Somatic Mutational Landscapes of Adherens Junctions and Their

1 Somatic mutational landscapes of adherens junctions and their

2 functional consequences in cutaneous melanoma development

4 Praveen Kumar Korla,1 Chih-Chieh Chen,2 Daniel Esguerra Gracilla,1 Ming-Tsung Lai,3 Chih-

5 Mei Chen,4 Huan Yuan Chen,5 Tritium Hwang,1 Shih-Yin Chen,4,6,* Jim Jinn-Chyuan Sheu1,4, 6-9,*

6 1Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 80242, Taiwan;

7 2Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung 80424,

8 Taiwan; 3Department of Pathology, Taichung Hospital, Ministry of Health and Welfare, Taichung

9 40343, Taiwan; 4Genetics Center, China Medical University Hospital, Taichung 40447, Taiwan;

10 5Institute of Biomedical Sciences, Academia Sinica, Taipei 11574, Taiwan; 6School of Chinese

11 Medicine, China Medical University, Taichung 40402, Taiwan; 7Department of Health and

12 Nutrition Biotechnology, Asia University, Taichung 41354, Taiwan; 8Department of

13 Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; 9Institute of

14 Biopharmaceutical Sciences, National Sun Yat-sen University, Kaohsiung 80242, Taiwan

16 PKK, CCC and DEG contributed equally to this study.

17 *Correspondence to: Dr. Shih-Yin Chen ([email protected]) at Genetics Center, China

18 Medical University Hospital, Taichung, 40447, TAIWAN; or Dr. Jim Jinn-Chyuan Sheu

19 ([email protected]) at Institute of Biomedical Sciences, National Sun Yat-sen

20 University, Kaohsiung City 80424, TAIWAN.

22 Running title: mutational landscape of cadherins in melanoma

23 Abstract

24 Cell-cell interaction in skin homeostasis is tightly controlled by adherens junctions (AJs).

25 Alterations in such regulation lead to melanoma development. However, mutations in AJs and

26 their functional consequences are still largely unknown.

27 Methods: Cadherin mutations in skin cutaneous melanoma were identified using sequencing data

28 from TCGA dataset, followed by cross-validation with data from non-TCGA cohorts. Mutations

29 with significant occurrence were subjected to structural prediction using MODELLER and

30 functional protein simulation using GROMACS software. Neo-antigen prediction was carried out

31 using NetMHCpan tool. Cell-based fluorescence reporter assay was used to validate β-catenin

32 activity in the presence of cadherin mutations. Clinical significance was analyzed using datasets

33 from TCGA and other non-TCGA cohorts. Targeted gene exon sequencing and

34 immunofluorescence staining on melanoma tissues were performed to confirm the in silico

35 findings.

36 Results: Highly frequent mutations in type-II classical cadherins were found in melanoma with

37 one unique recurrent mutation (S524L) in the fifth domain of CDH6, which potentially destabilizes

38 Ca2+-binding and cell-cell contacts. Mutational co-occurrence and physical dynamics analyses

39 placed CDH6 at the center of the top-four mutated cadherins (core CDHs; all type-II), suggesting

40 altered heterophilic interactions in melanoma development. Mutations in the intracellular domains

41 significantly disturbed CDH6/β-catenin complex formation, resulting in β-catenin translocation

42 into cytosol or nucleus and dysregulation of canonical Wnt/β-catenin signaling. Although

43 mutations in core CDH genes correlated with advanced cancer stages and lymph node invasion,

44 the overall and disease-free survival times in those patients were longer in patients with wild-type.

45 Peptide/MHC-I binding affinity predictions confirmed overall increased neo-antigen potentials of

46 mutated cadherins, which associated with T-lymphocyte infiltration and better clinical outcomes

47 after immunotherapy.

48 Conclusion: Changes in cell-cell communications by somatic mutations in AJ cadherins function

49 as one of mechanisms to trigger melanoma development. Certain mutations in AJs may serve as

50 potential neo-antigens which conversely benefit patients for longer survival times.

52 Keywords: adherens junctions (AJ), cadherin-6 (CDH6), somatic mutation, melanoma, neo-

53 antigen

55 Graphical Abstract

57 Heterophilic interactions between melanocyte and keratinocyte maintain skin homeostasis. UV-

58 induced CDH mutations cause contact control loss from keratinocyte and melanomagenesis.

59 During metastasis, mutation-derived Neo-Ags boost T-lymphocytes and activate anti-cancer

60 immunity.

61 Introduction

62 Cutaneous melanoma is the most dangerous form of skin cancer with high invasive and metastatic

63 potentials, resulting in more than 55,000 deaths per year worldwide [1] . Even though the cure rate

64 for patients with localized tumors is high, the overall five-year survival rates could be very low

65 (<20%) for those in whom the spread has occurred, indicating critical roles of cell-cell and cell-

66 matrix crosstalk in disease development. In normal epidermis, melanocytes or their stem cells form

67 multiple contacts with keratinocytes, which in turn establish regulatory networks in paracrine

68 manners to fine-tune melanocyte growth and epidermal homeostasis [2, 3]. During

69 melanomagenesis, melanoma cells alter such regulatory contacts via extracellular matrix

70 remodeling and then promote dermal invasion by activating inflammation-dependent cell

71 migration/translocation [4]. These findings suggest that loss of the control by keratinocytes enables

72 melanocyte undergoing uncontrolled cell growth, leading to cell transformation and melanoma

73 development.

74 Adherens junctions (AJs) are cadherin-based dynamic structures which link the physical

75 contact from the extracellular matrix to cytoskeleton networks via complex formation between

76 cadherins and catenins (,  and p120-catenin). Dissociation of -catenin by growth factor

77 stimulation leads to loss of cadherin-mediated cell-cell contact and increase of -catenin levels in

78 cytoplasm and nucleus, which subsequently promotes cell proliferation via activating TCF/Wnt

79 signaling [5, 6]. On the other hand, AJs also regulate stress-sensing and force-transmission through

80 signaling cascades, known as mechanotransduction [7, 8]. Clustering of core cadherin-catenin

81 complexes can further strengthen cell-cell adhesion, allowing cadherins to nucleate signaling hubs

82 and establish the regulatory Hippo network [9, 10]. Breakdown of Hippo network by up-regulating

83 expression and nuclear translocation of YAP/TAZ, the nuclear mechanosensor/transducer, was 4

84 found during melanoma progression, resulting in invasion, metastasis and drug resistance [11-14].

85 Accordingly, AJ-mediated mechanical and cytoskeletal signaling are important for melanoma to

86 create 3D microenvironment for further progression.

87 Recent studies by using lineage-tracing approach or global gene expression analyses

88 suggested that skin cutaneous melanoma cells may originate from adult melanocyte stem cells and

89 show feature properties of multipotent progenitors [2, 4]. Within the specialized anatomical

90 microenvironments, both hemophilic (via type-I cadherins) and heterophilic (via type-II cadherins)

91 cell-cell interactions are required for melanocyte stem cells to develop new cell partnerships with

92 stroma and/or endothelial cells. For examples, cadherin switching from N-cadherin (CDH2) to K-

93 cadherin (CDH6) was found critical for neural crest cell formation, emigration and detachment

94 from the neural tube to be melanocyte [15, 16]. Furthermore, down-regulation of key junction

95 proteins for communication between melanocytes and keratinocytes frequently occur during

96 melanoma development, including E-cadherin (CDH1) and P-cadherin (CDH3) [2, 17, 18].

97 Alterations in such interacting network enable melanocyte stem cells to proliferate and migrate out

98 of the niche after activation or transformation by extrinsic stimuli like UV exposure [2, 4].

99 With advanced whole genome sequencing and other integrative technologies, a set of major

100 driver mutations in cutaneous melanoma, e.g. BRAF, RAS and NF1, have been discovered which

101 contribute to activation of mitogen-activated protein kinase and phosphoinositol kinase signaling

102 [19, 20]. Notably, immune signatures with higher lymphocyte infiltration have been correlated

103 with improved survival outcomes but are irrespective of the genomic subtypes in patients [19, 21].

104 These data indicate the need to further explore certain genes that determine microenvironment

105 remodeling and lymphocyte recruitment through cell-cell/cell-matrix interactions. In this study,

106 we aimed to study somatic mutational landscapes of key AJ genes in melanoma and characterize

107 functional impacts of those mutations with molecular and clinical meanings.

108 Materials and Methods

109 Data collection and functional relevance with mutations in classical cadherin genes

110 Somatic mutation, gene expression and clinical information data of individual cadherins in skin

111 cutaneous melanoma were collected from cBioPortal databank (https://www.cbioportal.org/) Data

112 from TCGA cohort (TCGA, PanCancer Atlas; n = 448) were utilized as the studying cohort, and

113 the resultant data were validated by using data from non-TCGA cohort (n = 396). The functional

114 interactome among classical cadherins were analyzed by using STRING protein-protein

115 interactome database (http://string-db.org/). Oncoprinter and Mutation mapper tools in cBioportal

116 database were performed to analyze mutation types, hotspot mutation sites, and the conserved

117 mutation sites in cadherin and CTNNB1 genes [22]. To map the key pathways associated with

118 cadherin mutations, normalized gene expression data were applied for gene set enrichment analysis

119 (GSEA) by using GSEA Java (version 2.2.3) from Broad Institute [23]. Prediction of peptide-

120 binding affinity onto MHC-I complex, with the peptide length of nine amino acids, was performed

121 to estimate the neo-antigen potentials of mutations in cadherin genes by using NetMHCpan

122 algorithm [24]. Mutation-containing peptides with antigen-tolerance score less than 1.0 were

123 considered as neo-antigens.

124

125 Tissue sample collection for targeted exon sequencing and immunofluorescence staining

126 Twenty-two skin cutaneous melanoma tissue blocks were collected from Department of Pathology,

127 Taichung Hospital, Ministry of Health and Welfare, Taiwan with an approved IRB study (109028)

128 by the Institutional Review Board of Tsaotun Hospital, Ministry of Health and Welfare, Taiwan.

129 Genomic DNA was extracted from those tissue blocks using QIAamp DNA FFPE Tissue Kit

130 (Qiagen, Venlo, Netherlands), followed by PCR enrichment to establish ﬁnal DNA libraries for

131 targeted exon sequencing (cadherin genes involved in the core interactome) on a HiSeq 2000

132 (Illumina, San Diego, CA). The raw sequencing data were filtered by Cutadapt to obtain clean data

133 for further quality control checks [25]. By using SAMtools, somatic mutations occurred in classic

134 CDHs were identified with an average depth more than 120 counts and an average coverage more

135 than 60% on each chromosome [26]. Among the 22 tissues, 9 of them showed mutations in

136 classical cadherin genes in the Taiwanese cohort (Table S1).

137 For immunofluorescence staining, tissue sections were dewaxed by xylene, followed by

138 alcohol fixation and rehydration. After antigen retrieval in 10 mM citric acid buffer (pH 6.0) and

139 blocking with 5% BSA, tissue sections were incubated with Abs against different core CDHs and

140 co-stained with anti-β-catenin Abs (Cat# MAB14489; Abnova Corp., Taipei, Taiwan) at 4oC for

141 overnight. The Abs against core CDHs were anti-CDH6 (PAB31388; Abnova Corp.), anti-CDH9

142 (PA5-106548; Thermo Fisher Scientific Inc., Waltham, MA), anti-CDH10 (ab196662; Abcam

143 PLC., Cambridge, UK) and anti-CDH18 (A14645; Abclonal Inc., Woburn, MA) Abs. For T-

144 lymphocyte infiltration study, anti-CD3 Abs (A19017; Abclonal Inc.) were utilized to co-stain

145 with anti-β-catenin Abs. Secondary Ab staining was carried out by using FITC-conjugated anti-

146 rabbit IgG (for core CDHs and CD3; sc-2359; Santa Cruz Biotech. Inc., Dallas, TX) and CFL555-

147 conjugated anti-mouse IgG (for β-catenin; sc-362267; Santa Cruz Biotech. Inc.) Abs at 37oC for 1

148 hour. Auto-fluorescence were quenched using True VIEW auto-fluorescence quenching kit

149 (Vector Lab., Burlingame, CA). Cell nuclei in the tissues were counterstained with DAPI and the

150 images were taken under an IX83 fluorescence microscope (Olympus Corp., Shinjuku, Japan).

151

152 Structural prediction of the cadherin-6 (CDH6) protein 8

153 The three-dimensional structures of extracellular cadherin domain 5 (EC5; residues 487-608),

154 juxtramembrane domain (JMD; residues 660-677), and catenin-binding domain (CBD; residues

155 687-784) of CDH6 protein were predicted by using the MODELLER program (version 9v8) [27].

156 In this study, CDH6 (PDB ID: 5VEB) was selected as the template for predicting the structure of

157 S524L-EC5, p120-catenin in complex with E-cadherin (PDB ID: 3L6X) was selected as template

158 for predicting the structures of WT-, D661N-, and E662K-JMD in complex with p120-catenin,

159 and β-catenin with desmosomal-cadherin (PDB ID: 3IFQ) was selected as the other template for

160 predicting the structures of WT-, R689Q-, D691N-, E722K-, D726N-, S749F-, R773Q-CBD in

161 complex with β-catenin. The qualities of all modeled structures were assessed through

162 Ramachandran plots. The steepest descent algorithm was used for structural optimization, and

163 PyMOL (http://www.pymol.org/) was used for all three-dimensional (3D) structures and charge

164 distribution presentation.

165

166 Molecular dynamics simulations

167 Molecular dynamics (MD) simulations were performed using GROMACS software (version 5.1.4)

168 [28]. The OPLS-AA force field was used for energy calculations. The models were solvated with

169 TIP3P water molecules and simulated in a cubic box with periodic boundary conditions. The

170 energy of the models was first minimized using the steepest descent algorithm. The simulations

171 were performed in the canonical NVT and NPT ensembles through the position-restrained MD

172 simulation for 100 ps, respectively. The linear constraint solver algorithm was used to constrain

173 the bonds. The MD simulations were performed at constant pressure and temperature for 30 ns

174 using an integration time step of 2 fs. The non-bonded interactions were cutoff at 10 Å. The

175 coordinates from the MD simulations were saved every 10 picosecond.

176

177 Binding free energy calculation

178 The pmx tool was used to construct the hybrid topologies of the system used in the free energy

179 calculations [29]. This tool automatically generates hybrid structures and topologies for amino

180 acid mutations that represent the two physical states of the system. The double system (combine

181 both branches of a thermodynamic cycle) in a single simulation box was used as the setup to keep

182 the system neutral at all times during a transition (Figure S1) [29]. After obtaining this hybrid

183 structure, free energy simulations were performed using GROMACS. From the 10-ns equilibrated

184 trajectories, 100 snapshots were extracted, and a rapid 100-ps simulation was performed starting

185 from each frame. The lambda (λ) ranged from 0 to 1 and from 1 to 0 for the forward and backward

186 integrations, respectively, thus describing the interconversion of the WT to MT systems and the

187 MT to WT systems, respectively. Finally, the pmx tool was used to integrate over the multiple

188 curves and subsequently estimate free energy differences using the fast-growth thermodynamic

189 integration approach, which relies on the Crooks–Gaussian Intersection (CGI) protocol [30]. In

190 such a double-system/single-box setup, the estimated free energy corresponds to the ΔΔG of

191 binding (Figure S1).

192

193 Clinical association study and statistical analyses

194 Clinical data of melanoma patients, including tumor stage, lymph node invasion, metastasis,

195 lymphocyte score and survival time, were retrieved from TCGA database. GraphPad Prism

196 (GraphPad software, La Jolla, CA) was utilized for statistical analyses. Patients were divided into

197 WT CDHs (no mutation in any cadherin genes) and MT core CDHs (patients with mutation in top-

198 four highly-mutated cadherin genes) groups. Statistical differences between two groups were

199 estimated by t-test. Kaplan–Meier method was used to estimate survival curves, and a log-rank

200 test was performed for statistical comparison between two groups. To compare neo-antigen

201 potentials, two-way ANOVA was utilized to compare differences between two groups with

202 multiple mutation sites.

203

204 Gene cloning and site-directed mutagenesis

205 The gene segment of β-catenin was amplified by nested PCR using cDNA from human melanoma

206 A375 cells. After purification, the gene segment was further sub-cloned into pmCherry-N1 vector

207 (Clontech Lab., Madison. WI), thus the gene is tagged with an mCherry at C-terminal end. Human

208 CDH6 cDNA (OriGene Technologies, Inc., USA) was amplified and sub-cloned into pAcGFP1-

209 N1 vector (Clontech Lab.) to generate GFP-tagged wild type CDH6. CDH6 with mutations in the

210 CBD domain were generated by site directed mutagenesis (F541; Thermo Fisher Scientific Inc.).

211 DNA sequencing was done to confirm the gene sequences and the introduced substitutions that are

212 in-frame with the fusion partners.

213

214 Cell-based complex formation assay between -catenin with CDH6 and its mutant variants

215 To monitor complex formation in live cells, -catenin-mCherry and CDH6 variants gagged with

216 GFP were co-transfected into A375 cells using Lipofectamine 2000 (Thermo Fisher Scientific

217 Inc.) by 1:1 molar ratio. Complex formation and cellular localization were determined by an

218 IX83 fluorescent microscope (Olympus Corp., Shinjuku, Japan) 24 hours after gene transfection.

219 Cell image and fluorescent intensity were analyzed using Image-Pro Premier (Media Cybernetics

220 Inc., Rockville, MD).

221 Results

222 Highly-frequent mutations in adherens junction (AJ) cadherin genes in melanoma

223 Dysregulation in interactions between melanocyte and keratinocyte or melanocyte and matrix is a

224 key step during melanoma malignant transition. We therefore wanted to know mutational profiles

225 of major adhesion molecules, mainly adherens junction (AJ) molecules, in melanoma and their

226 biological impacts on cancer progression (Figure 1). A total of 20 classical cadherins that

227 participate in cell-cell interactions are identified in human genome [31]. STRING protein-protein

228 interactome analyses defined a compact network composed by 16 classical cadherins (6 type-I and

229 10 type-II) that determines AJ organization, homophilic cell adhesion via plasma membrane

230 adhesion molecules, and cell junction assembly with significant scores (q-values < 10-5) (Figure

231 2A). TCGA-melanoma data with 448 sequenced tumor samples were utilized to analyze mutation

232 statuses of those 16 genes by using cBioportal databank [32]. Surprisingly, frequent mutations (>

233 10%) were found in 5 classical cadherin genes (CDH6, CDH18, CDH10, CDH9 and CDH4)

234 (Figure 2B). Although no mutually exclusive pattern, genetic alterations in the classic cadherin

235 genes sum up a total mutation rate of 56% in melanoma tissues. Consistent with previous findings

236 indicating rare E-cadherin (CDH1) mutations in cancer [33], only 2.7% of melanomas carry CDH1

237 mutations. In addition, no mutation was found in P-cadherin (CDH3). Mutation rates in other

238 minor AJ genes including nectins and nectin-like molecules were also relatively low (< 10%)

239 (Figure S2), suggesting that mutations in classical cadherins play more important roles in

240 melanoma development. Such conclusions can be further validated by using sequencing data from

241 non-TCGA cohort, especially for CDH6, CDH9, and CDH18 genes which also show mutation

242 rates larger than 10% (Figure S3). Significantly, the top-four mutated genes (core CDHs) are all

243 type-II classical cadherins, suggesting alterations in heterophilic interactions may function as one

244 possible mechanism to drive melanoma development. At nucleotide levels, most of the detected

245 substitutions (around 90%) were G to A or C to T, a signature for DNA damage repair after UV-

246 induced DNA adducts [19] (Figure 2C), indicating the etiological relevance of mutations in those

247 adhesion genes during melanoma development [4].

248

249 Cadherin mutations in melanoma development

250 Mutational profiles revealed that somatic mutations in cadherins could be detected at a variety of

251 positions throughout coding regions with the existence of some truncations and out-of-frame

252 insertions/deletions (Figure 3A, left panel). The feature of most detected somatic mutations

253 suggests a tumor suppressor role for those adhesion proteins in cancer development [34].

254 Nevertheless, the S524L substitution on the fifth extracellular (EC5) domain of CDH6 (K-cadherin)

255 stood out to be a unique mutation with a relatively higher frequency, indicating its potent role in

256 melanoma development. Especially, this recurrent missense mutation can be confirmed by the non-

257 TCGA cohort (Figure 3A, right panel). On the other hand, mutations in the intracellular domains

258 of top-five cadherins show mutual exclusivity with β-catenin (CTNNB1) mutations (Figure 3B),

259 suggesting potent effects of cadherin mutations on canonical Wnt/β-catenin signaling.

260 Co-occurrence analysis among the core CDHs (CDH6, CDH9, CDH10 and CDH10)

261 indicated the association of CDH6 mutations with mutations in CDH9, CDH10 and CDH18

262 (Figure 3C). Gene expression profiling using the GEO dataset (GDS1965) indicated relatively high

263 levels of core CDHs during melanoma malignant transition (Figure 3D). Such expression patterns

264 can be also confirmed at protein levels by immunofluorescence staining (Figures S4-S7). Through

265 biophysical dynamics approach, previous study confirmed strong heterophilic interactions among

266 these core CDHs, and CDH6 was the only one that can form stable hemophilic interactions with

267 other three [35]. Interestingly, CDH6 was also the only one to be expressed predominantly in

268 normal melanocytes but not in normal squamous epithelial cells (Figure S4, upper). The above

269 data suggested CDH6 as the key player among the core CDHs during melanoma development and

270 progression (Figure 3E). Thus, mutations in type-II cadherins, especially in CDH6, may gain

271 functional advantages during melanoma development.

272

273 Structural dynamics of the S524L substitution on the fifth extracellular (EC5) domain of

274 CDH6 (K-cadherin) and the potential impacts on Ca2+-binding/stabilization

275 To know functional impacts of mutations in CDH6, the structure of the EC5 domain (CDH6-EC5)

276 was constructed by MODELLER program using the published human CDH6 crystal structure

277 (Protein Data Bank ID: 5VEB) as the template. To compare the similarity in three-dimensional

278 structure of the EC5, Root-Mean-Square Deviation (RMSD) analyses indicated longer average

279 distances between the atoms in the S524L mutant as compared to wild type (WT) CDH6,

280 suggesting its impacts on the EC5 structure (Figure 4A, upper). Analyses of the residue-specific

281 Root-Mean-Square Fluctuations (RMSF) (Figure 4A, lower) further revealed higher atomic

282 fluctuations of the S524L mutant at the β2/β3 loop, a region for Ca2+-binding, when compared

283 with the WT. The 4/β5 loop, which was predicted to stabilize the Ca2+-binding, was also found

284 less stable in this mutant due to its higher RMSF and B-factors (Figure 4A-B). To confirm this,

2+ 𝑆524𝐿 285 free energy differences of Ca -binding between WT and S524L (∆∆𝐺𝐵𝑖𝑛𝑑𝑖𝑛𝑔) was calculated in a

286 series of alchemical free energy simulations by using CGI protocol [30]. The double-free energy

287 was calculated according to ΔG1 (Ca2+-bound) – ΔG2 (Ca2+-free), as shown in the thermodynamic

288 cycle (Figure 4C). The data indicated that the Ca2+-binding affinity toward CDH6-EC5 was

289 reduced by S524L substitution (ΔΔG = 4.4 kJ/mol). These analyses conclude that S524L

290 substitution may induce additional fluctuations in the β2/β3 and β4/β5 loop regions, which can

291 promote instability in this region and thus hamper Ca2+-binding.

292

293 Mutations in the intracellular regions of cadherins (CDH-C) and their effects on catenin-

294 binding

295 The process of AJ assembly to establish cell-cell contacts involves complex formation between

296 cadherins and catenins. To study functional roles of mutations in the intracellular domain (CDH-

297 C), we performed sequence alignment across cadherins involved in the cadherin interactome core.

298 Based on structural and functional analyses, CDH-C can be divided into two major domains: the

299 juxtramembrane domain (JMD) and the catenin-binding domain (CBD) that can bind to p120-

300 catenin (-catenin) and -catenin, respectively (Figure 5A). Most of mutations (>85%) were found

301 involved in the binding regions or conversed residues, indicating potential impacts on cytoplasmic

302 complex formation. We next predicted 3-D structures of CDH6-JMD (residues 660-677) and

303 CDH6-CBD (residues 687-784) in complexes with p120-catenin and -catenin, respectively, in

304 which orange spheres indicate the mutations (Figure 5B). Significantly, most of the mutations can

305 change the charge (D661N, E662K, R689Q, D691N, E722K, D762N, and R773Q); therefore, the

306 salt bridge interactions between cadherins and catenins can be interrupted, which may

307 consequently reduce cadherin/catenin complex formation.

308 The cadherin-catenin binding free energy differences between WT and MT structures were

309 calculated by using CGI protocol [30]. The catenin binding affinity differences (∆∆𝐺 )

310 were calculated according to ΔG1 (catenin-bound) – ΔG2 (catenin-free), as shown in the

311 thermodynamic cycle when placed in one simulation box (Figure S1A). The net change of the

312 simulation box was considered as zero and negative ΔΔG values indicate stabilizing mutations 15

313 (Figure S1B). The resulting binding free energy differences (∆∆𝐺 ) in mutants as compared

314 to WT CDH6 were 4.60 (D661N) and 7.50 (E662K) kJ/mol for p120-catenin (Figure 5C and

315 Figure S8), whereas 8.17 (R689Q), 5.96 (D691N), -0.07 (E722K), 5.98 (D762N), and 8.70 (R773Q)

316 kJ/mol for -catenin (Figure 5C and Figure S9), suggesting that the binding affinity for both p120-

317 catenin and -catenin were disrupted in most mutants (∆∆𝐺 0). The residue S749 lies

318 within the invariant cadherin sequence 749Ser-Leu-Ser-Ser-Leu753, which has been shown as an

319 important phosphorylation site to form hydrogen bonds with -catenin [36]. The S749F

320 substitution therefore can block the phosphorylation in this region, and consequently reduce

321 cadherin/-catenin complex formation. Similar strategies were also applied to calculate cadherin-

322 catenin binding free energy differences caused by somatic mutations in other top-four mutated

323 genes. Except CDH10, most substitutions in JMD and CBD domains of those type-II CDHs

324 resulted in less stable cadherin-catenin complexes with increased free energy differences (Table

325 S2).

326

327 Mutations in the CDH-C of CDH6 and their functional consequences

328 To study the functional relevance, GFP-tagged CDH6 mutants with different known mutations in

329 CDH-C were prepared individually and co-transfected with wild type -catenin tagged with

330 mCherry into A375 cells, a melanoma cell line proven to express the lowest CDH6 level in cell

331 line screening. As shown in Figure 6A-B, wild type CDH6 was predominantly expressed on the

332 cell surface in complex with -catenin. Except D691N, CDH6 mutants with mutations in -

333 catenin-binding domain significantly reduced complex formation on cell membrane by promoting

334 -catenin translocation into cytosol and/or nucleus, indicating destabilization of CDH6/-catenin

335 complex. For D661N and E662K, the portions of nuclear -catenin were also increased, which

336 could be due to indirect effects of unstable CDH6/p120-catenin complex formation (Figure 6A-

337 B).

338 To know clinical and biofunctional impacts, we used dual-color immunofluorescence

339 staining to confirm protein expression patterns of core CDHs and -catenin in clinical samples.

340 For melanoma cells with wild type CDHs, the-catenin staining usually co-localized with CDH

341 staining on the cell surface. However, nuclear and cytosol -catenin staining as found in the cell-

342 based study can be frequently detected in melanoma samples with mutated core CDHs (Figure 6C

343 and Figures S4-S7). We also analyzed mRNA levels of genes involved in Hippo and Wnt/-catenin

344 signaling in patients with mutations in top-four cadherins (MT core CDHs). Patients without any

345 mutation in classical cadherin genes (WT CDHs) were used as the controls. The Hippo-

346 transcription factor TEAD4 was found significantly up-regulated (p = 0.0034) in MT core CDHs

347 group which associated with activation of target genes, including BIRC5 (p = 0.0004) and WNT1

348 (p = 0.0291) (Figure 6D). The Wnt/-catenin signaling responsive genes WNT1 (p = 0.0291) and

349 FOSL1 (p = 0.0012) were also found up-regulated. Coordination among TEAD4, FOSL1, BIRC5

350 and WNT1 was previously implicated in YAP/Tead-mediated cancer migration/invasion and ion

351 metabolism [37, 38]. C-MYC, WISP1 and PPARD were slightly increased but did not reach

352 statistical significance.

353

354 Clinical significance of cadherin mutations during melanoma development

355 To address the translational relevance, we performed clinical association study by subgrouping

356 patients into MT core CDHs and WT CDHs groups. Our data revealed that patients in the MT

357 group are at higher risks to get more aggressive tumors at advanced stages (stage III/IV) (p = 0.010; 17

358 Figure 7A, left) and lymph node invasion (p = 0.021; Figure 7A, middle). Although we found

359 higher tendency of metastasis for the MT group (6.2 % vs. 5.1 %; Figure 7A, right), the data did

360 not reach statistical significance. Surprisingly, such tumor-promoting activity did not determine

361 worse survival outcomes. In general, patients with mutations in core CDH genes showed better

362 overall (p = 0.008; Figure 7B, upper) and disease-free (p = 0.002; Figure 7B, lower) survival times.

363 To know possible signaling signatures in melanomas with mutations in core CDH genes, gene set

364 enrichment analysis (GSEA) was performed using WT group as the control. Several up-regulated

365 pathways were found to contribute to cancer progression, DNA replication/cell proliferation, and

366 cell cycle regulation (Table S3 and Figure S10), indicating the pro-oncogenic activity of cadherin

367 mutations. These data may explain why melanomas with cadherin mutations correlate with

368 advanced tumor stages and metastatic potentials.

369 Interestingly, T-lymphocyte-up and antigen response pathways were also found to be

370 activated in MT group (Figure 7C), suggesting that anti-tumor immune responses may be triggered

371 once tumor cells enter the circulation system. Consistent with those findings, patients in MT group

372 showed higher lymphocyte scores (including lymphocyte density and distribution) in their tumor

373 lesions as compared to patients in the control group (Figure 7D). To confirm such finding in real

374 clinical samples, melanoma tissue sections with matched genetic information (Table S1) were

375 utilized to detect T-lymphocytes (CD3+; red) in melanomas. Our data revealed higher T-

376 lymphocyte (CD3+) infiltrations in melanoma lesions with mutations in core CDH genes as

377 compared to tissues with wild type CDHs (Figure 7E). Our data suggest that cadherin mutations

378 can potentially trigger anti-cancer immunity in patients via promoting lymphocyte infiltration,

379 resulting in prolonged survival times.

380

381 Cadherin mutations generate neo-antigens that favor better immunotherapy outcomes

382 To understand how cadherin mutations activate T-cell immunity, we used machine-learning-based

383 neo-antigen prediction program, NetMHCpan [24], to score neo-antigen potentials of defined

384 mutations. Notably, the recurrent S524L substitution on CDH6 was found to be a potent neo-

385 antigen due to increased MHC-I binding affinity and less antigen-tolerance (Figure 8A).

386 Predictions on other three core cadherins confirmed an overall decrease of antigen-tolerance scores

387 associated with known somatic mutations (Figure S11). This finding indicated higher

388 immunogenic potentials generated by mutations in core CDH genes. Accumulating evidence have

389 revealed that tumors with higher mutational burdens correlate with the likelihood of higher neo-

390 antigen loads, leading to better therapeutic outcome for patients after immunotherapy [39, 40]. By

391 using immunogenetic datasets from MSKCC and UCLA groups [39, 41], we found that mutations

392 in core CDH genes highly correlated with total mutational and neo-antigen loads in patients with

393 metastatic melanoma (Figure 8B-C). Those findings suggest an anti-tumor microenvironment

394 immune type associated with mutations in core CDH genes that favors a better clinical response

395 to immunotherapeutic agents (Figure S12) [42]. To confirm this, we also compared clinical

396 outcomes of anti-CTLA4 (Ipilimumab) [39] and anti-PD1 (Pembrolizumab) [41] therapies

397 between patients with and without mutations in core CDH genes. Consistent with higher

398 mutational and neo-antigen loads, patients with CDH mutations usually showed longer therapeutic

399 duration times for Ipilimumab treatment (Figure 8D) and better drug responses for Pembrolizumab

400 therapy (Figure 8E).

401 Discussion

402 Alterations in cell-cell contacts have long been considered as an important determinant of cancer

403 initiation and progression. Although molecular bases of many well-known cadherins e.g. CDH1

404 (E-cadherin) and CDH2 (N-cadherin) in cancer development have been established, we know very

405 little about genetic/functional impacts of other AJ genes on cancer especially cutaneous melanoma,

406 a unique cancer type with a high mutation load. Through data mining using TCGA dataset, we

407 discovered high mutation frequencies in cadherin genes which can be validated by using data from

408 non-TCGA cohort (Figure 2 and Figure S3A). Interestingly, we found the top-four highly mutated

409 genes (core CDHs, including CDH6, CDH18, CDH10 and CDH9) are all type-II cadherins which

410 harbor the capability to form heterophilic interactions. By contrast, mutation frequencies in type-I

411 cadherins, which form homophilic interactions, were relatively low. Even though mutation rate of

412 CDH4 (R-cadherin) was also high (the fifth highly mutated gene) and defined as a type-I cadherin,

413 the heterophilic interaction between CDH4 and CDH2 has been previously reported [43]. Dislike

414 CDH1 being genetically deleted or epigenetically silenced during cancer development, those top-

415 four cadherins were consistently expressed to form cell-cell contacts during the transition from

416 melanocyte to melanoma. Our study therefore provides genetic evidence to support the view that

417 the heterophilic interactions between different cell types, such as melanocytes with keratinocytes

418 or stroma cells, play critical roles in skin tissue homeostasis. Breaking such balance by mutations

419 in key cadherins may serve as a newly-defined driving force to promote melanomagenesis, which

420 could be a possible common mechanism shared by other cancer types. Pan-cancer study of AJ

421 genetic alterations is under investigation.

422 Among AJ genes in cutaneous melanoma, CDH6 stood out to be a very interesting one

423 which showed the highest mutation rate with several novel functional mutations. Through cadherin

424 binding dynamics assays [35], CDH6 was also found at the center of the interactome formed by

425 the top-four core CDHs. Previous study has shown CDH6 a node protein for the interplay of

426 multiple cellular signaling such as TGF-, PI3K/AKT and FAK/ERK1/2, thus participates in the

427 regulation of stem cell formation and function [44, 45]. Both tumor-suppressing [46, 47] and pro-

428 oncogenic activities [45, 48, 49] were associated with CDH6 expression in cancer development.

429 Emerging evidence in recent years suggest a pro-EMT role of CDH6 to promote cancer invasion

430 and metastasis [48, 49]. Those controversial results signify complex regulation in inter-/intra-tissue

431 crosstalk during cancer development and progression. Based on our study, recurrent mutation

432 S524L and functional mutations in the intracellular domain of CDH6 can result in loss of cell-cell

433 contacts and -catenin translocation into nucleus, which associate with tumors at more advanced

434 stages and lymph node invasion (Figures 6 and 7), suggesting those mutations as active drivers but

435 not passengers during melanogenesis. To our knowledge, this is the first report to address the

436 functional impacts of CDH6 and its mutations on melanoma development. Interestingly, we also

437 found nuclear staining for mutated CDH6 in tumor samples (Figure 6C), which could be novel

438 phenomena in certain types of melanoma awaiting for further investigation.

439 Type II cadherins have been shown to exhibit either homophilic or heterophilic binding

440 capability in cell aggregation studies [50-52] and their interactions define the development of

441 nervous system in vivo [51, 53, 54]. Expression of specific complements of type II cadherins in

442 neuron cells can determine their cell sorting during embryonic development into distinct sub-

443 populations with different phenotypes/functions [55]. It has been known that melanocytes as well

444 as their stem cells in the skin originate from neural crest cells migrating out along the dorsal neural

445 tube. In this process, changing cell-cell contacts by cadherin switching plays important roles to

446 trigger cell de-polarization and epithelial–mesenchymal transition, leading to cell detachment and

447 migration [56, 57]. The well-known type-II cadherins involved in the underlying mechanisms

448 include CDH6 [15], CDH7 [58], and CDH11 [59]. Recent studies on biophysics of collective cell

449 migration revealed that cancer cell metastasis is a process very similar to neural crest cell spreading

450 [60-62]. This viewpoint highlights the requirement of changes in heterotypic mechanical

451 interactions for cells to pass through the mechanical barriers generated by primary cell-cell

452 contacts in the original tissue. For examples, fibroblast-like synoviocytes can migrate and invade

453 into pigmented villonodular synovitis by expressing CDH11 [63], Silencing of CDH10 was also

454 found as another mechanism to enhance breast tumor cell mobility in hypoxic conditions [64].

455 These studies support our findings that mutations in core type-II cadherins may provide advantages

456 for melanoma cells to alter the original connecting networks with keratinocytes, enabling them to

457 further migrate out of melanocyte stem cell niche and form tumor lesions on the skin.

458 Based on genetic analyses, molecular modeling and experimental investigations, our data

459 highly suggest the causal consequence of mutations in CDH-C domains with activation of Wnt/-

460 catenin signaling. Firstly, mutations in CDH-C domains of the core CDHs showed mutual

461 exclusivity with β-catenin (CTNNB1) mutations (Figure 3B), suggesting that they share redundant

462 biological functions; secondly, CDH-C mutations correlated with increased thermodynamics of

463 the CDH-C/-catenin or CDH-C/p120-catenin complexes (Figure 5C and Figures S8-S9),

464 indicating higher levels of free -catenin in cells; finally, live imaging study confirmed an overall

465 increased nuclear -catenin in cells expressing CDH6 mutants with mutations in the CDH-C

466 domain (Figure 6A-B). Consistent with this, the recurrent S524L mutation in CDH6-EC5 also

467 affect the stability and organization of CDH6-mediated AJ complex (Figure 4A-C), leading to -

468 catenin release from the membrane and translocation into cell nucleus as well as loss of contact

469 inhibition (Figure 6B-D). Especially, there is a 510-His-Ala-Val-512 (HAV) motif at the EC5

470 domain which is considered responsible for stabilization and clustering of adjacent cadherin

471 monomers in a calcium-dependent fashion [65, 66]. Also, the EC5 is the only extracellular domain

472 that contains critical cysteine residues (at the positions of 497, 589, 591, and 600) in CDH6 for

473 possible cis- and trans-dimerization of neighboring cadherins. Therefore, S524L mutation may

474 restrain calcium-induced CDH6 rigidification and dimerization, leading to reduced cell contacts

475 with neighboring cells.

476 Although mutations in the core CDH genes showed pro-oncogenic activity, patients with

477 such mutations showed better overall and disease-free survival times (Figure 7B). These results

478 indicate possible complications associated with mutations in those type-II cadherins in controlling

479 immunosurveillance. Several cadherins including CDH6 were identified as RGD motif-containing

480 proteins, which can function as ligands to activate metastasis-associated integrins, including 1-

481 containing integrins such as α2β1, and promote cancer cell proliferation, migration and invasion

482 [67-69]. Signaling activated by those metastasis-associated integrins can also enhance tumor

483 angiogenesis [68-70]. By contrast, activation of 1-containing integrins in T cells, a specialized

484 skin-resident/infiltrating T cells, can also promote cell adhesion to endothelial cells, extravasation

485 and lymphocyte infiltration into tumors [71-73]. T cells trigger immune response rapidly just

486 like innate-like lymphocytes do, yet they can direct the development of adaptive immunity with

487 TCR-dependent reactivity/specificity [74, 75]. By using the immunogenetic dataset from MSKCC

488 group [39], we also noticed patients with mutations in CDH6 or other core CDH genes showed

489 more γδT cell recruitments in melanoma lesions with more activated CD4+ memory T cells and

490 higher cytolytic scores (Figure S12). Accordingly, there could be a possibility that mutations in

491 cadherins, when the melanoma cells spread through the blood or lymph, can stimulate T cell

492 activation and enhance lymphocyte recruitment into core tumor lesions, leading to up-regulation

493 of T-lymphocyte and antigen responses which were evidenced in our study (Figure 7C-E).

494 A recent study indicated increased hydrophobicity of UV-derived mutations that can

495 enhance antigen presentation on the MHC complexes with stronger neo-antigen potentials [76].

496 Since most of detected CDH mutations in melanoma are highly relevant to UV exposure, CDH

497 mutations should play certain key roles in triggering anti-tumor immunity in patients. Especially,

498 the S524L substitution in CDH6 has been predicted to be a strong neo-antigen (Figure 8A),

499 peptides with such substitution could be utilized as potent adjuvants to trigger stronger anti-

500 melanoma immunity when co-treated with other immuno-therapeutics such as anti-PD-1/L1 or

501 anti-CTLA4 Abs. Whether mutations in cadherins can change cytokine profiles in the local

502 microenvironment to direct lymphocyte homing and activate anti-melanoma immunity will be

503 investigated in our future study.

504 Some limitations in this study need to be addressed here. Firstly, the mutational profiles

505 detected in the Taiwanese cohort were found a little bit different from the TCGA cohort which is

506 Caucasian dominant (96%) [19]. Those differences suggest the involvement of genetic factors

507 between different populations during melanomagenesis. However, CDH6, CDH10, CDH18 are

508 still within the top-five most frequently mutated cadherin genes in the Taiwanese cohort (Table

509 S1). Also, most of detected mutations are related to UV-exposure (G to A or C to T substitutions).

510 Therefore, protein staining data by using Taiwanese samples might be relevant but mutation sites

511 are different. Tumor samples from Caucasian population with matched genetic information may

512 provide the opportunity to confirm biological effects of those mutations shown in Figure 6A-B.

513 Secondly, CDH mutations alone may not be the only contributor to make melanoma becoming

514 more immunogenic. Functional impacts from other genetic events during melanoma development

515 should be also considered and investigated.

516 Abbreviations

517 AJs: adherens junctions; CDH: cadherin; core CDHs: the top-four mutated cadherins including

518 CDH6, CDH9, CDH10 and CDH18; Neo-Ag: neo-antigen; GSEA: gene set enrichment analysis;

519 EC5: extracellular cadherin domain 5; JMD: juxtramembrane domain; CBD: catenin-binding

520 domain; MD: molecular dynamics; WT: wild type; MT: mutant type; ΔΔG: free energy

521 differences.

522

523 Acknolwedgments

524 The authors thank technical assistance from Mr. Louice Chun-Chi Lai at National Sun Yat-sen

525 University/Taiwan. The authors also thank critical comments from Prof. Daniel Riveline at

526 IGBMC/France, Prof. Kuang-Hung Cheng at National Sun Yatsen University/Taiwan, and Prof.

527 Anna C Jan at National Cheng Kung University/Taiwan. This study was supported by grants from

528 Ministry of Science and Technology (MOST)/Taiwan (106-2314-B-110-001-MY3; 109-2314-B-

529 110-003-MY3; 108-2811-B-110-506; 108-2221-E-110-061-MY2), Ministry of Health and

530 Welfare/Taiwan (MHW 10819), China Medical University Hospital (DMR-108-121), and the

531 NSYSU-KMU joint research projects (108-P013).

532

533 Author contributions

534 CCC, SYC and JJCS designed the experiments and validated the data. PKK, DEG, MTL, HYC

535 and TH performed bioinformatics and clinical association study. CCC and PKK performed

536 molecular modeling and free-energy calculation. DEG, CMC, and TH made the gene constructs,

537 conducted cell-based studies, and analyzed the data. CCC, PKK, DEG, MTL, SYC and JJC

538 confirmed the data and wrote the manuscript.

539

540 Competing Interests

541 The authors declare no competing interests in this study.

542

543 Data availability

544 Data from the experiments presented in this study are included in this published article and its

545 Supplementary Information file. Other data generated or analyzed during this study are also

546 available from the corresponding authors on request.

547 Supplementary Materials

548 Table S1. Genetic mutation rates of core CDH genes based on targeted exon sequencing in

549 melanoma samples from Taiwanese patients

550 Table S2. Calculation of catenin-binding free energy differences between WT and known

551 mutations in core CDH genes in melanoma

552 Table S3. Gene set enrichment analyses of reactomes/pathways concurrently up-regulated with

553 mutations in top-four core CDH genes in melanoma

554 Figure S1. Double-system/single-box setup

555 Figure S2. Mutations in nectin and nectin-like genes in skin cutaneous melanoma

556 Figure S3. Validation of mutation frequencies in key adherens junction (AJ) genes in non-TCGA

557 cohort

558 Figure S4. Dual-color immunofluorescence staining of CDH6 and -catenin on melanoma tissues

559 from Taiwanese patients

560 Figure S5. Dual-color immunofluorescence staining of CDH9 and -catenin on melanoma tissues

561 from Taiwanese patients

562 Figure S6. Dual-color immunofluorescence staining of CDH10 and -catenin on melanoma

563 tissues from Taiwanese patients

564 Figure S7. Dual-color immunofluorescence staining of CDH18 and -catenin on melanoma

565 tissues from Taiwanese patients

566 Figure S8. The predicted CDH6/p120-catenin (-catenin) complex structures and their binding

567 free energy differences (ΔΔG) between WT and MT CDH6

568 Figure S9. The predicted CDH6/-catenin complex structures and their binding free energy

569 differences (ΔΔG) between WT and MT CDH6

570 Figure S10. Reactomes/pathways associated with mutations in top-four highly mutated cadherin

571 (core CDHs) genes in skin cutaneous melanoma

572 Figure S11. Neo-antigen potentials of mutations in core CDH genes in skin cutaneous melanoma.

573 Figure S12. Changes of tumor microenvironments in skin cutaneous melanoma by mutations in

574 core CDH genes

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754 74. Davey MS, Willcox CR, Joyce SP, Ladell K, Kasatskaya SA, McLaren JE, et al. Clonal 755 selection in the human Vdelta1 T cell repertoire indicates gammadelta TCR-dependent 756 adaptive immune surveillance. Nat Commun. 2017; 8: 14760. 757 75. Fay NS, Larson EC, Jameson JM. Chronic Inflammation and gammadelta T Cells. Front 758 Immunol. 2016; 7: 210. 759 76. Pham TV, Boichard A, Goodman A, Riviere P, Yeerna H, Tamayo P, et al. Role of 760 ultraviolet mutational signature versus tumor mutation burden in predicting response to 761 immunotherapy. Mol Oncol. 2020; 14: 1680-94.

762

1. NGS Data Collection • Collect NGS data of melanoma samples (including gDNA and mRNA) from TCGA (n=448) and non-TCGA (n=396) cohorts through cBioportal (www.cbioportal.org)

2. NGS Data Analysis • Mutation mapping and identification of recurrent or conserved mutations using Oncoprint and Mutation mapper • Mutation validation by using data from non-TCGA cohorts • Key pathways of mRNA expression defined by GSEA (Gene Set Enrichment Analysis) method (www.genepattern.org)

3. In Silico Functional Prediction • 3-D structural predictions by MODELLER program • Molecular dynamics simulations (RMSD and RMSF) by GROMACS software • Binding free energy calculation according to CGI protocol by GROMACS software • Neo-Ag predictions of somatic mutations by NetMHCpan tool (www.cbs.dtu.dk/services/NetMHCpan)

4. Cell-Based Functional Validation • Gene cloning of CDH6 (fused with GFP) and -catenin (mCherry) • Site-directed mutagenesis to introduce known mutations in CDH6 • Gene transfection and protein co-localization analysis

5. Clinical Relevance Analysis • Clinical association study, including tumor stage, lymph node invasion, metastasis, lymphocyte scores, overall/disease-free survivals, and immunotherapy responses • Mutation validation by targeted gene sequencing on melanomas • Fluorescent staining on tissue sections/microarrays 763

764 Figure 1. The workflow scheme presents the whole process of data mining and functional 765 characterizations in this study.

766

767 Figure 2. Mutations in classical cadherin genes in skin cutaneous melanoma. (A) STRING 768 protein-protein interaction analysis (https://string-db.org) on 20 annotated classical cadherins 769 reveals an interactome composed of 16 classical cadherins (6 type-I and 10 type-II) involved in AJ 770 organization, homophilic cell adhesion via plasma membrane adhesion molecules, and cell 771 junction assembly pathways. (B) Mutation frequencies of the cadherin genes in skin cutaneous 772 melanoma were analyzed by using NGS data from the TCGA cohort (TCGA, PanCancer Atlas; n 773 = 448). Our data showed no mutation in CDH3. (C) The heat map indicates nucleotide substitution 774 profiles of mutated cadherin genes in skin cutaneous melanoma. 36

775

776

777 Figure 3. Biological relevance of mutations in classical cadherin genes in skin cutaneous 778 melanoma. (A) Lollipop plots of mutations in classical cadherin genes in skin cutaneous 779 melanoma were presented by using NGS data from TCGA cohort (n = 448) (left) and the non- 780 TCGA cohort (n = 396) (right). The non-TCGA cohort includes patients from Broad/Dana Farber 781 (n = 26, Nature 2012), MSKCC (n = 64, NEJM 2014), Broad (n = 121, Cell 2012), Yale (n = 147, 782 Nat Genet 2012), and UCLA (n = 38, Cell 2016). (B) Mutations in the intracellular domains of 783 top-five cadherin genes were compared with mutations in CTNNB1. (C) Co-occurrence analysis 784 among top-four type-II classical cadherin genes (core CDHs) including CDH6, CDH9, CDH10, 785 and CDH18. (D) Gene expression levels of core CDHs during melanoma malignant transition from

786 normal neural crest cells and melanocytes to melanoma. Gene expression data were extracted from 787 the GEO dataset (GDS1965). (E) Physical interactions (heterophilic/homophilic) among the top- 788 four core CDHs were previously characterized and confirmed [35].

789

790

791 Figure 4. Impact of S524L mutation on the fifth extracellular (EC5) domain of the CDH6 792 protein. (A) Protein stability of wild type (WT) and mutant (S524L) CDH6 were compared by 793 residue-specific Root-Mean-Square Deviation (RMSD) and Root-Mean-Square Fluctuations 794 (RMSF) methods in simulations. The S524L mutation lead to higher instability in the 2/3 loop 795 and 4/5 loop regions. (B) The EC5 structures of the WT and S524L CDH6 are drawn in cartoon 796 putty representation, where the color is ramped by residue from blue as the lowest B-factor value 797 to red as the highest B-factor value. In addition, the size of the tube also reflects the value of the 798 B-factor, where the larger the B-factor the thicker the tube. The calcium atoms and mutation sites 799 are indicated with gray sphere and yellow sphere representations, respectively. (C) The 800 thermodynamic cycle for Ca2+ binding affinity was calculated in one simulation box. The free 801 energy difference in Ca2+ binding corresponds to a double free energy difference: ΔΔG = ΔG1 – 802 ΔG2.

803

804 805 Figure 5. Thermo-stability of CDH6/catenin complex with mutations in the intracellular 806 domain (CDH-C) of CDH6. (A) Alignment of CDH-C protein sequences among classical 807 cadherins. Letters with underlines and yellow shadows indicate known mutations in the CDH-C 808 sequences in skin cutaneous melanoma based on the NGS data from TCGA cohort. Letters with 809 orange color represent the conserved residues whereas letters in red color represent identical 810 residues among classical cadherins. Green box and red box indicate the regions of JMD for p120-

811 catenin (-catenin) and CBD for -catenin binding, respectively. (B) The complex structures of 812 CDH6-JMD (blue)/p120-catenin (green) (left) and CDH6-CBD (blue)/-catenin (green) (right) 813 were predicted by using the MODELLER program. The mutation sites are highlighted in orange 814 spheres. (C) The binding free energy differences (ΔΔG) caused by mutations in the domains of 815 JMD for p120-catenin binding (upper) and CBD for -catenin binding (lower) were calculated by 816 using the fast-growth thermodynamic integration approach.

817 818 819 Figure 6. Functional impacts of mutations in the intracellular domain (CDH-C) of CDH6 on 820 -catenin binding. (A) Wild type (WT) CDH6 and its mutants (tagged with GFP) were co- 821 transfected with -catenin (tagged with mCherry) into A375 cells. Cells expressing both green and 822 red constructs were monitored and representative images were taken under a fluorescent 823 microscope 24 hrs after transfection. (B) Distributions of -catenin in cells with different CDH6 824 constructs were counted and categorized into nucleus, cytoplasm and membrane (n = 50 cells for 825 each CDH6 construct). (C) Dual-color immunofluorescence staining, CDH6 in red and -catenin 826 in green, was performed on melanoma tissue slides from patients with wild type cadherins and 827 patients with D724N mutation in CDH6. (D) Gene expression levels of genes involved in Hippo 828 (blue box) and Wnt/-catenin (pink box) pathways were compared between patients with 829 mutations in top-four core cadherins (MT core CDHs) and patients without mutation in any 830 classical cadherins (WT CDHs). The expression levels of indicated genes were extracted from the 831 mRNA data of TCGA cohort. Statistical differences between two groups were compared by using

832 t-test. The p values were presented as *: p value < 0.05, **: p value < 0.01, and ***: p value < 833 0.001.

834

835 836 837 Figure 7. Clinical significance of cadherin mutations during melanoma development. (A) 838 Clinical associations were compared between patients with mutations in top-four core cadherins 839 (MT core CDHs) and patients without any mutation in classical cadherin genes (WT CDHs), 840 including tumor stage (left), lymph node invasion (middle), and metastasis (right). (B) Kaplan- 841 Meier analyses were performed to compare overall survival (upper) and disease-free survival 842 (lower) between MT core CDHs and WT CDHs groups. (C) Gene set enrichment analysis (GESA) 843 was performed using mRNA expression data from TCGA group. Two pathways, T-lymphocyte- 44

844 up (upper) and antigen response (lower), were found positively associated with mutations in top- 845 four core CDH genes. (D) Lymphocyte scores in melanoma tissues of TCGA cohort were 846 compared between MT core CDHs and WT CDHs groups. (E) Dual-color immunofluorescence 847 staining, CD3 in red and-catenin in green, was performed on melanoma tissue slides from 848 patients with wild type cadherins and patients with K467R mutation in CDH6 (left). CD3+ T- 849 lymphocytes in the stained tissue sections were quantified and compared between MT core CDHs 850 and WT CDHs groups (right). For data in (A), (D) and (E), Fisher’s exact test was performed to 851 analyze the clinical association. For (B), the long-rank test was used to compare the survival times. 852 The p values were presented as *: p value < 0.05, **: p value < 0.01, and ***: p value < 0.001.

A mutation count wild type score mutant type score

1000 8 8 counts Mutation

100 6 6

Normal 10 self-antigen 14 4

0.1 S524L 2 2 0.01 Potential

neo-antigen 0.0010 0

Antigen tolerance score 0 100 200 300 400 500 600 700 Amino acid position on CDH6

B MSKCC, NEJM 2014 UCLA, Cell 2016 C MSKCC, NEJM 2014 UCLA, Cell 2016 MSKCC, NEJM 2014 p = 0.0001*** MSKCC,p = NEJM0.0049** 2014 MSKCC,p = 0.0034** NEJM 2014 MSKCC,p = 0.0001***NEJM 2014 4000 5000 3000 6000

4000 3000 2000 4000 3000 2000 2000 1000 2000 1000 1000 Mutational load NeoAntigen load 0 0 0 0 WT MT Core WT MT Core WT MT Core WT MT Core DE Ipilimumab (anti-CTLA-4)圖表標題 effects Pembrolizumab (anti-PD-1)圖表標題 response

WT2 21 21 WT2 9 12

MT core1 16 6 MT core1 11 5

0%0% 20% 20% 40% 40% 60% 60% 80% 80% 100% 100% 0% 20% 20% 40% 40% 60% 60% 80% 80% 100% 100% 數列1 數列2 數列1 數列2 Effective more than 2 years Responder Effective less than 2 years Non-responder MSKCC, NEJM 2014; p = 0.0401* UCLA, Cell 2016; p = 0.0485* 853 854 855 Figure 8. Immunogenicity of cadherin mutations and therapeutic advantages for treating 856 melanoma. (A) The mutation counts (gray bars) for known CDH6 mutations in TCGA cohort 857 were shown alone with the amino acid positions in CDH6. Antigen tolerance scores of the 858 indicated mutation (red square) and its corresponding wild type (green circle) were analyzed by 859 using NetMHCpan algorithm and plotted on this bar chart. Immunogenetic datasets of MSKCC 860 [39] and UCLA [41] were utilized to compare (B) overall mutational loads; (C) Neo-antigen loads; 861 (D) therapeutic duration times for Ipilimumab (anti-CTLA-4) treatment; and (E) drug responses 862 for Pembrolizumab (anti-PD-1) therapy between MT core CDHs and WT CDHs groups. For data 863 in (B) and (C), Fisher’s exact test was performed to analyze the statistical significances. For (D) 864 and (E), two-proportions Z-Test was utilized to compare drug effectiveness. The p values were 865 presented as *: p value < 0.05, **: p value < 0.01, and ***: p value < 0.001.

Table S1. Genetic mutation rates of core CDH genes based on targeted exon sequencing in melanoma samples from Taiwanese patients Gene Extracellular domain Substitution eventsa Intracellular domain Substitution eventsa Total mutation rate and transmembrane mutation rate (%) (%) (cases/ total mutation rate (%) samples) CDH6 9.09% exon9:c.A1400G:p.K467R 18.18% exon12:c.G2170A:p.D724N 22.73% exon12:c.G2236A:p.V746M (5/22) CDH10 18.18% exon3:c.C346G:p.R116G 9.09% exon12:c.G2044A:p.E682K 22.73% exon3:c.C377T:p.T126I (5/22) exon5:c.G607A:p.E203K exon7:c.C1163T:p.S388F

CDH18 13.63% exon4:c.G310A:p.D104N 13.63% exon16:c.G2345A:p.G782E 22.73% exon8:c.G1124A:p.G375E (5/22) exon9:c.G455A:p.G152E CDH12 18.18% exon6:c.C28T:p.L10F 0% None detected 18.18% exon6:c.C65T:p.P22L (4/22) exon12:c.T1301C:p.I434T exon15:c.G1802A:p.C601Y exon16:c.C2186T:p.T729I CDH9 9.09% exon2:c.C62T:p.T21I 0% None Detected 13.63% exon4:c.G541A:p.V181I (3/22) CDH24 9.09% exon3:c.C395T:p.P132L 4.54% exon13:c.G2036A:p.R679Q 13.63% exon3:c.C470T:p.A157V (3/22) exon8:c.G1279A:p.E427K CDH1 9.09% exon8:c.C1082T:p.A361V 4.54 exon14:c.G2287A:p.E763K 9.09% exon10:c.G1483A:p.V495M (2/22) CDH2 4.54% exon9:c.G1276A:p.D426N 9.09% exon15:c.G2476A:p.A826T 9.09% exon11:c.C1725A:p.F575L exon16:c.T2593G:p.S865A (2/22) CDH4 9.09% exon1:c.C44T:p.P15L 0% None detected 9.09% exon14:c.A2338C:p.I780L (2/22) CDH5 9.09% exon4:c.C556T:p.H186Y 0% None detected 9.09% exon11:c.G1798A:p.A600T (2/22) CDH7 9.09% exon3:c.G433A:p.D145N 4.54% exon12:c.C2264T:p.S755F 9.09% exon11:c.G1789A:p.E597K (2/22) exon11:c.G1864A:p.V622M CDH8 9.09% exon3:c.G340A:p.V114I 0% None detected 9.09% exon3:c.C445G:p.P149A (2/22) exon10:c.A1589C:p.Y530S CDH11 9.09% exon3:c.C65T:p.A22V 0% None detected 9.09% exon5:c.G607A:p.E203K (2/22) CDH13 4.54% exon5:c.C557T:p.S186F 9.09% exon14:c.C2143T:p.P715S 9.09% exon6:c.G760A:p.V254I exon14:c.G2170A:p.V724I (2/22) CDH15 4.54% exon9:c.G1306A:p.V436M 0% Not detected 4.54% (1/22) ac- chromosomal base substitution; p- amino acid substitution Table S2. Calculation of catenin-binding free energy differences between WT and known mutations in core CDH genes in melanoma Binding ∆∆𝑮𝑴𝒖𝒕𝒂𝒕𝒊𝒐𝒏 Mutation Protein Domain 𝑩𝒊𝒏𝒅𝒊𝒏𝒈 protein (kJ/mol) D661N CDH6, CDH9, CDH10 JMD p120-catenin 4.60 ± 0.69 E662K CDH6, CDH9 JMD p120-catenin 7.50 ± 2.11 G663E CDH18 JMD p120-catenin 42.29 ± 7.57 G665R CDH10 JMD p120-catenin -15.34 ± 13.85 E666K CDH9 JMD p120-catenin 21.95 ± 4.39 E667K CDH18 JMD p120-catenin 1.56 ± 2.88 R689Q CDH6 CBD -catenin 8.17 ± 4.91 D691N CDH6 CBD -catenin 5.96 ± 0.96 E722K CDH6 CBD -catenin -0.07 ± 5.04 D726N CDH6 CBD -catenin 5.98 ± 1.77 D733N CDH9 CBD -catenin 15.62 ± 1.83 E741K CDH9 CBD -catenin 16.38 ± 2.35 G742E CDH10 CBD -catenin -19.63 ± 6.25 L767F CDH10 CBD -catenin -1.60 ± 5.56 R773Q CDH6, CDH9 CBD -catenin 8.70 ± 5.05

Table S3. Gene set enrichment analyses of reactomes/pathways concurrently up-regulated with mutations in top-four core CDH genes in melanomaa NOM Reactome /Pathwayb ES NES p-value 1. Liver_Cancer_Subclass_G3_Up 0.6493 1.7587 0.0159 2. Doxorubicin_Resistance_Up 0.7836 1.6533 0.0175 3. Antigen_Response 0.6726 1.7603 0.0236 4. Thyroid_Carcinoma_Anaplastic_Up 0.5938 1.7737 0.0276 5. T_Lymphocyte_Up 0.7554 1.6582 0.0320 6. Epithelial_Mesenchymal_Transition_Up 0.6731 1.7110 0.0333 7. M_G1_Transition 0.6640 1.6491 0.0345 8. Core_Serum_Response_Up 0.6037 1.6801 0.0352 9. Cell_Cycle_Mitotic 0.6362 1.6307 0.0369 10. Synthesis_Of_DNA 0.6648 1.6498 0.0381 11. Mitotic_G1/G1_S_Phases 0.5985 1.6321 0.0386 12. CDC20_Mediated_Degradation_Of_Mitotic_Proteins 0.6666 1.6343 0.0423 13. DNA_Replication 0.6606 1.6724 0.0437 14. Mitotic_M/M_G1_Phases 0.6589 1.6693 0.0437 15. Cervical_Cancer_Proliferation_Cluster 0.6992 1.6660 0.0483 aAbbreviations: ES, enrichment score; NES, normalized enrichment score; NOM p-value, nominalized p-value. bReactomes or pathways with NOM p-values < 0.05 were considered as significantly relevant with mutations in top-four core CDH genes.

Figure S1. Double-system/single-box setup. (A) Two branches of a thermodynamic cycle are placed in one simulation box. The different boxes in the scheme are indicated by the solid (𝜆 0) and broken (𝜆1) lines. (B) An example of a simulation setup for the catenin binding free energy calculation. The free energy difference corresponds to a double free energy difference: ΔΔG = ΔG1 – ΔG2.

Figure S2. Mutations in nectin and nectin-like genes in skin cutaneous melanoma. (A) Mutation frequencies and (B) mutational profiles of nectin and nectin-like genes in skin cutaneous melanoma were analyzed by using NGS data from the TCGA cohort (TCGA, PanCancer Atlas; n = 448).

Figure S3. Validation of mutation frequencies in key adherens junction (AJ) genes in non- TCGA cohort. Mutation frequencies of key AJ genes, including (A) top-five highly-mutated cadherin genes identified in TCGA cohort, (B) nectin and (C) nectin-like genes, were analyzed by using NGS data from non-TCGA cohort (n = 396). The non-TCGA cohort include patients from Broad/Dana Farber (n = 26, Nature 2012), MSKCC (n = 64, NEJM 2014), Broad (n = 121, Cell 2012), Yale (n = 147, Nat Genet 2012), and UCLA (n = 38, Cell 2016).

Figure S4. Dual-color immunofluorescence staining of CDH6 and -catenin on melanoma tissues from Taiwanese patients. Tissue sections were prepared from Taiwanese patients with melanoma. Dual-color immunofluorescence staining, red for CDH6 and green for -catenin, was performed on melanocyte from normal skin epithelium counterpart (upper), melanoma with wild type CDHs (middle), and melanoma with D724N mutation (lower). Cell nuclei were counterstained with DAPI.

Figure S5. Dual-color immunofluorescence staining of CDH9 and -catenin on melanoma tissues from Taiwanese patients. Tissue sections were prepared from Taiwanese patients with melanoma. Dual-color immunofluorescence staining, red for CDH9 and green for -catenin, was performed on melanocyte from normal skin epithelium counterpart (upper), melanoma with wild type CDHs (middle). Cell nuclei were counterstained with DAPI.

Figure S6. Dual-color immunofluorescence staining of CDH10 and -catenin on melanoma tissues from Taiwanese patients. Tissue sections were prepared from Taiwanese patients with melanoma. Dual-color immunofluorescence staining, red for CDH10 and green for -catenin, was performed on melanocyte from normal skin epithelium counterpart (upper), melanoma with wild type CDHs (middle), and melanoma with E682K mutation (lower). Cell nuclei were counterstained with DAPI.

Figure S7. Dual-color immunofluorescence staining of CDH18 and -catenin on melanoma tissues from Taiwanese patients. Tissue sections were prepared from Taiwanese patients with melanoma. Dual-color immunofluorescence staining, red for CDH18 and green for -catenin, was performed on melanocyte from normal skin epithelium counterpart (upper), melanoma with wild type CDHs (middle), and melanoma with G782E mutation (lower). Cell nuclei were counterstained with DAPI.

Figure S8. The predicted CDH6/p120-catenin (-catenin) complex structures and their binding free energy differences (ΔΔG) between WT and MT CDH6. (A) The predicted structure of JMD (residues 660-677, in blue) in complex with p120-catenin (-catenin, in green) was generated by using the MODELLER program. The known mutated sites, D661 and D662, on the JMD (in orange) were found to interact with K444 and K574 on the p120-catenin, respectively. (B) A double-system/single-box setup was used to estimate the binding free energy differences (ΔΔG) caused by mutations.

Figure S9. The predicted CDH6/-catenin complex structures and their binding free energy differences (ΔΔG) between WT and MT CDH6. (A) The predicted structure of CBD (residues 687-784, in blue) in complex with -catenin (green) was generated by using MODELLER program. The known mutated sites were highlighted in orange spheres. A double- system/single-box setup was used to estimate the binding free energy differences (ΔΔG) caused by (B) R689Q, (C) D691N, (D) E722K, (F) E726N, and (G) R773Q substitutions. Cartoon representations indicated the binding interfaces between mutated residues on CBD (yellow) and the interacting residues on -catenin.

Figure S10. Reactomes/pathways associated with mutations in top-four highly mutated cadherin (core CDHs) genes in skin cutaneous melanoma. Gene set enrichment analysis (GSEA) was performed using mRNA expression data from the TCGA group (TCGA, PanCancer Atlas; n = 448). Patients without mutations in any cadherin genes were utilized as the controls. Concurrent up-regulated reactomes with p-values less than 0.05 were shown here. Two pathways, Antigen Response and T-Lymphocyte Up, were also shown in Fig. 7C. A CDH9 CDH9 wild type score p = 0.0148* WTmutant type score 120120 MT

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00 1 2 3 4 5 6 7 8 9 0 1 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 3 3 32 33 34 35 36 37 38 39 40 41 G86E I201K G54D L446F S749L S143L S734L S450L P452L L533P V474F E120K E140K E741K E156K E662K E666K E708K P269S E375K E498K E643K H111Y Y659H D748E R133K D744N R773C R127C D151N D661N D733N G310E G327E N464D D515N D574N D592N R267Q G742W amino acid substitutions in CDH9 B CDH10 CDH10 wild type score p = 0.0030** mutantWT type score 120120 MT

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00 1 2 3 4 5 6 7 8 9 3 5 7 10 11 12 1 14 15 16 17 18 19 20 21 22 23 24 2 26 27 28 29 30 31 32 33 34 35 36 3 38 39 40 41 42 43 44 45 46 47 N59K H50R R51C D81N G69R I132N I690N L765F L279F L480V P487L S387F S421F S597F E121K P170S E214K P357S A462V P606S E648K P698S F391C H112Y D712Y Y306N D539Y H394Y R230K N466K G740E D152N G243S G363E R424H G520S G580S D649N D659N E683G R307Q G553R R638Q G663R R699W amino acid substitutions in CDH10 C CDH18 CDH18 wild type score p = 0.0070** mutantWT type score 120120 MT

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0 Antigen-tolerance score score Antigen-tolerance 0 score Antigen-tolerance Antig 1 2 3 4 5 6 7 8 9 0 1 6 7 3 0 3 9 0 4 6 1 1 12 13 14 15 1 1 18 19 20 21 22 2 24 25 26 27 28 29 3 31 32 3 34 35 36 37 38 3 4 41 42 43 4 45 4 47 K52E H78P D82E R50C M303I P535L P679L P730L T559A E144K E230K E379K E394K E543K E653K E666K E694K E714K V402A E426K P452S E498K D711Y K114N R226K R325K R555K D105N D109N G175S G204E G314E K340Q D376N D562N N545D G662E D754N D763N G768E D467H G192R R598Q G520R R652W amino acid substitutions in CDH18

Figure S11. Neo-antigen potentials of mutations in core CDH genes in skin cutaneous melanoma. Antigen-tolerance scores of known mutations in the extracellular domain of (A) CDH9; (B) CDH10; and (C) CDH18 were analyzed by using NetMHCpan algorithm and compared with the scores with wild type sequence. Substitutions with lower scores indicate higher neo-antigen potentials. Two-way ANOVA was utilized to compare the differences between wild type and mutant type. Statistical significance: *, p < 0.05; **, p < 0.01.

A CDH6 p = 0.0013** p = 0.0096** p = 0.0953 p = 0.0076** 250 400 300 400

200 300 300 200 150 200 200 100 100 100 100 50 0

Macrophages M1 0 NK cells activated 0 T cells gamma delta 0 -100 -100 -100 -50 WT CDHs MT core WT CDHs MT core WT CDHs MT coreT cells CD4 memory activated WT CDHs MT core

1500 p = 0.0188* 400 p = 0.0498* 300 p = 0.1031 300 p = 0.0011**

300 200 1000 200 200 100 500 100 0

T cells CD8 0 Monocytes 100 0 Cytolytic Score -100 -100 T cells follicular helper -500 -200 -200 0 WT CDHs MT core WT CDHs MT core WT CDHs MT core WT CDHs MT core

B core CDHs p = 0.0145* p = 0.0414* p = 0.1942 p = 0.0285* 250 400 300 400

200 300 300 200

150 200 200 100 100 100 100 50 0 0 0 Macrophages M1 NK cells activated T cells gamma delta 0 -100 -100 -100

-50 T cells CD4 memory activated WT CDHs MT core WT CDHs MT core WT CDHs MT core WT CDHs MT core

p = 0.0749 p = 0.1003 p = 0.0490* p = 0.0258* 1500 400 400 300

300 300 1000 200 200 200 500 100 100

0 0 T cells CD8 Monocytes 100 0 Cytolytic Score -100 -100 T cells follicular helper -500 -200 -200 0 WT CDHs MT core WT CDHs MT core WT CDHs MT core WT CDHs MT core

Figure S12. Changes of tumor microenvironments in skin cutaneous melanoma by mutations in core CDH genes. Microenvironment immune types were analyzed in tumors with mutations in (A) CDH6 or (B) core CDH genes, and compared with the data in tumors with wild type CDHs. The immune scores include T cells, M1 macrophages, activated NK cells, activated CD4+ memory T cells, CD8+ T cells, monocytes, follicular helper T cells and cytolytic score.