RB1 Genetic Alterations in Estrogen Receptor-Positive Breast Carcinomas: Correlation With Neuroendocrine Differentiation.

Genetic alterations in the retinoblastoma susceptibility gene (RB1) are present in up to 40% of triple-negative breast cancers (BCs) and frequent in tumors with neuroendocrine differentiation, including small cell neuroendocrine carcinoma. Data on RB1 genetic alterations in estrogen receptor (ER)-positive BCs are scarce. In this study, we sought to define the morphologic, immunohistochemical, and genetic features of ER-positive BCs harboring somatic alterations in RB1, with emphasis on neuroendocrine differentiation. ER-positive BCs with pathogenic RB1 genetic alterations were identified in <1% of cases (N = 55) from a cohort of 6026 BCs previously subjected to targeted next-generation sequencing, including 23 primary BCs (pBCs) and 32 recurrent/metastatic BCs (mBCs). In cases where loss of heterozygosity of the wild-type RB1 allele could be assessed (93%, 51/55), most pBCs (82%, 18/22) and mBCs (90%, 26/29) exhibited biallelic RB1 inactivation, primarily through loss-of-function mutation and loss of heterozygosity (98%, 43/44). Upon histologic review, a subset of RB1-altered tumors exhibited neuroendocrine morphology (13%, 7/55), which correlated with expression of neuroendocrine markers (39%, 9/23) in both pBCs (27%, 3/11) and mBCs (50%, 6/12). Loss of Rb protein expression was observed in BCs with biallelic RB1 loss only, with similar frequency in pBCs (82%, 9/11) and mBCs (75%, 9/12). All cases with neuroendocrine marker expression (n = 9) and/or neuroendocrine morphology (n = 7) harbored biallelic genetic inactivation of RB1 and exhibited Rb loss of expression. TP53 (53%, 29/55) and PIK3CA (45%, 25/55) were the most frequently comutated genes across the cohort. Overall, these findings suggest that ER-positive BCs with biallelic RB1 genetic alterations frequently exhibit Rb protein loss, which correlates with neuroendocrine differentiation in select BCs. This study provides insights into the molecular and phenotypic heterogeneity of BCs with RB1 genetic inactivation, underscoring the need for further research into the potential clinical implications associated with these tumors.

Nonlobular Invasive Breast Carcinomas with Biallelic Pathogenic CDH1 Somatic Alterations: A Histologic, Immunophenotypic, and Genomic Characterization.

CDH1 encodes for E-cadherin, and its loss of function is the hallmark of invasive lobular carcinoma (ILC). Albeit vanishingly rare, biallelic CDH1 alterations may be found in nonlobular breast carcinomas (NL-BCs). We sought to determine the clinicopathologic characteristics and repertoire of genetic alterations of NL-BCs harboring CDH1 biallelic genetic alterations. Analysis of 5842 breast cancers (BCs) subjected to clinical tumor-normal sequencing with an FDA-cleared multigene panel was conducted to identify BCs with biallelic CDH1 pathogenic/likely pathogenic somatic mutations lacking lobular features. The genomic profiles of NL-BCs with CDH1 biallelic genetic alterations were compared with those of ILCs and invasive ductal carcinomas (IDCs), matched by clinicopathologic characteristics. Of the 896 CDH1-altered BCs, 889 samples were excluded based on the diagnosis of invasive mixed ductal/lobular carcinoma or ILC or the detection of monoallelic CDH1 alterations. Only 7 of the 5842 (0.11%) BCs harbored biallelic CDH1 alterations and lacked lobular features. Of these, 4/7 (57%) cases were ER-positive/HER2-negative, 1/7 (14%) was ER-positive/HER2-positive, and 2/7 (29%) were ER-negative/HER2-negative. In total, 5/7 (71%) were of Nottingham grade 2, and 2/7 (29%) were of grade 3. The NL-BCs with CDH1 biallelic genetic alterations included a mucinous carcinoma (n = 1), IDCs with focal nested growth (n = 2), IDC with solid papillary (n = 1) or apocrine (n = 2) features, and an IDC of no special type (NST; n = 1). E-cadherin expression, as detected by immunohistochemistry, was absent (3/5) or aberrant (discontinuous membranous/cytoplasmic/granular; 2/5). However, NL-BCs with CDH1 biallelic genetic alterations displayed recurrent genetic alterations, including TP53, PIK3CA (57%, 4/7; each), FGFR1, and NCOR1 (28%, 2/7, each) alterations. Compared with CDH1 wild-type IDC-NSTs, NL-BCs less frequently harbored GATA3 mutations (0% vs 47%, P = .03), but no significant differences were detected when compared with matched ILCs. Therefore, NL-BCs with CDH1 biallelic genetic alterations are vanishingly rare, predominantly comprise IDCs with special histologic features, and have genomic features akin to luminal B ER-positive BCs.

Concurrent POLE hotspot mutations and mismatch repair deficiency/microsatellite instability in endometrial cancer: A challenge in molecular classification.

OBJECTIVE: Endometrial carcinoma (EC) has different molecular subtypes associated with varied prognosis. We sought to characterize the molecular features of ECs with POLE hotspot mutations and concurrent mismatch repair (MMR) deficiency/high microsatellite instability (MSI). METHODS: We identified POLE-mutated (POLEmut), MMR-deficient (MMRd)/MSI-high (MSI-H), or combined POLEmut/MMRd ECs subjected to clinical tumor-normal panel sequencing between 2014 and 2023. Clonality of somatic mutations, MSI scoring, tumor mutational burden (TMB), proportion of somatic insertions and deletions (indels), and single base substitution (SBS) mutational signatures were extracted. RESULTS: We identified 41 ECs harboring POLE exonuclease domain hotspot mutations, 138 MMRd and/or MSI-H ECs, and 14 POLEmut/MMRd ECs. Among the 14 POLEmut/MMRd ECs, 11 (79 %) exhibited clonal POLE hotspot mutations; 4 (29 %) had a dominant POLE-related mutational signature, 4 (29 %) displayed dominant MMRd-related signatures, and 6 (43 %) had mixtures of POLE, aging/clock, MMRd, and POLEmut/MMRd-related SBS mutational signatures. The number of single nucleotide variants was higher in POLEmut/MMR-proficient (MMRp) and in POLEmut/MMRd ECs compared to POLE wild-type (wt)/MMRd EC (both p < 0.001). Small indels were enriched in POLEwt/MMRd ECs (p < 0.001). TMB was highest in POLEmut/MMRd EC compared to POLEmut/MMRp and POLEwt/MMRd ECs (both p < 0.001). Of 14 patients with POLEmut/MMRd EC, 21 % had a recurrence, versus 10 % of those with POLEmut/MMRp EC. Similar findings were noted in 3 POLEmut ECs in patients with Lynch syndrome; akin to somatic POLEmut ECs, these tumors had high TMB. CONCLUSION: POLEmut/MMRd ECs may be genetically distinct. Further studies are needed to assess the impact on outcomes and treatment response within this population.

Predicting disease-causing variant combinations.

Notwithstanding important advances in the context of single-variant pathogenicity identification, novel breakthroughs in discerning the origins of many rare diseases require methods able to identify more complex genetic models. We present here the Variant Combinations Pathogenicity Predictor (VarCoPP), a machine-learning approach that identifies pathogenic variant combinations in gene pairs (called digenic or bilocus variant combinations). We show that the results produced by this method are highly accurate and precise, an efficacy that is endorsed when validating the method on recently published independent disease-causing data. Confidence labels of 95% and 99% are identified, representing the probability of a bilocus combination being a true pathogenic result, providing geneticists with rational markers to evaluate the most relevant pathogenic combinations and limit the search space and time. Finally, the VarCoPP has been designed to act as an interpretable method that can provide explanations on why a bilocus combination is predicted as pathogenic and which biological information is important for that prediction. This work provides an important step toward the genetic understanding of rare diseases, paving the way to clinical knowledge and improved patient care.

Genetic characterisation of adult primary pleomorphic uterine rhabdomyosarcoma and comparison with uterine carcinosarcoma.

AIMS: To characterise the genetic alterations in adult primary uterine rhabdomyosarcomas (uRMSs) and to investigate whether these tumours are genetically distinct from uterine carcinosarcomas (UCSs). METHODS AND RESULTS: Three tumours originally diagnosed as primary adult pleomorphic uRMS were subjected to massively parallel sequencing targeting 468 cancer-related genes and RNA-sequencing. Mutational profiles were compared with those of UCSs (n = 57) obtained from The Cancer Genome Atlas. Sequencing data analyses were performed using validated bioinformatic approaches. Pathogenic TP53 mutations and high levels of genomic instability were detected in the three cases. uRMS1 harboured a likely pathogenic YTHDF2-FOXR1 fusion. uRMS2 harboured a PPP2R1A hotspot mutation and amplification of multiple genes, including WHSC1L1, FGFR1, MDM2, and CCNE1, whereas uRMS3 harboured an FBXW7 hotspot mutation and an ANKRD11 homozygous deletion. Hierarchical clustering of somatic mutations and copy number alterations revealed that these tumours initially diagnosed as pleomorphic uRMSs and UCSs were similar. Subsequent comprehensive pathological re-review of the three uRMSs revealed previously unidentified minute pan-cytokeratin-positive atypical glands in one case (uRMS3), favouring its reclassification as UCS with extensive rhabdomyosarcomatous overgrowth. CONCLUSIONS: Adult pleomorphic uRMSs harbour TP53 mutations and high levels of copy number alterations. Our findings underscore the challenge in discriminating between uRMS and UCS with rhabdomyosarcomatous differentiation.

PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update.

We present here a full update of the PMut predictor, active since 2005 and with a large acceptance in the field of predicting Mendelian pathological mutations. PMut internal engine has been renewed, and converted into a fully featured standalone training and prediction engine that not only powers PMut web portal, but that can generate custom predictors with alternative training sets or validation schemas. PMut Web portal allows the user to perform pathology predictions, to access a complete repository of pre-calculated predictions, and to generate and validate new predictors. The default predictor performs with good quality scores (MCC values of 0.61 on 10-fold cross validation, and 0.42 on a blind test with SwissVar 2016 mutations). The PMut portal is freely accessible at http://mmb.irbbarcelona.org/PMut. A complete help and tutorial is available at http://mmb.irbbarcelona.org/PMut/help.

Understanding mutational effects in digenic diseases.

To further our understanding of the complexity and genetic heterogeneity of rare diseases, it has become essential to shed light on how combinations of variants in different genes are responsible for a disease phenotype. With the appearance of a resource on digenic diseases, it has become possible to evaluate how digenic combinations differ in terms of the phenotypes they produce. All instances in this resource were assigned to two classes of digenic effects, annotated as true digenic and composite classes. Whereas in the true digenic class variants in both genes are required for developing the disease, in the composite class, a variant in one gene is sufficient to produce the phenotype, but an additional variant in a second gene impacts the disease phenotype or alters the age of onset. We show that a combination of variant, gene and higher-level features can differentiate between these two classes with high accuracy. Moreover, we show via the analysis of three digenic disorders that a digenic effect decision profile, extracted from the predictive model, motivates why an instance was assigned to either of the two classes. Together, our results show that digenic disease data generates novel insights, providing a glimpse into the oligogenic realm.

DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins.

High-throughput sequencing methods are generating enormous amounts of genomic data, giving unprecedented insights into human genetic variation and its relation to disease. An individual human genome contains millions of Single Nucleotide Variants: to discriminate the deleterious from the benign ones, a variety of methods have been developed that predict whether a protein-coding variant likely affects the carrier individual's health. We present such a method, DEOGEN2, which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates. This extensive contextual information is non-linearly mapped into one single deleteriousness score for each variant. Since for the non-expert user it is sometimes still difficult to assess what this score means, how it relates to the encoded protein, and where it originates from, we developed an interactive online framework (http://deogen2.mutaframe.com/) to better present the DEOGEN2 deleteriousness predictions of all possible variants in all human proteins. The prediction is visualized so both expert and non-expert users can gain insights into the meaning, protein context and origins of each prediction.

DIDA: A curated and annotated digenic diseases database.

DIDA (DIgenic diseases DAtabase) is a novel database that provides for the first time detailed information on genes and associated genetic variants involved in digenic diseases, the simplest form of oligogenic inheritance. The database is accessible via http://dida.ibsquare.be and currently includes 213 digenic combinations involved in 44 different digenic diseases. These combinations are composed of 364 distinct variants, which are distributed over 136 distinct genes. The web interface provides browsing and search functionalities, as well as documentation and help pages, general database statistics and references to the original publications from which the data have been collected. The possibility to submit novel digenic data to DIDA is also provided. Creating this new repository was essential as current databases do not allow one to retrieve detailed records regarding digenic combinations. Genes, variants, diseases and digenic combinations in DIDA are annotated with manually curated information and information mined from other online resources. Next to providing a unique resource for the development of new analysis methods, DIDA gives clinical and molecular geneticists a tool to find the most comprehensive information on the digenic nature of their diseases of interest.

Multilevel biological characterization of exomic variants at the protein level significantly improves the identification of their deleterious effects.

MOTIVATION: There are now many predictors capable of identifying the likely phenotypic effects of single nucleotide variants (SNVs) or short in-frame Insertions or Deletions (INDELs) on the increasing amount of genome sequence data. Most of these predictors focus on SNVs and use a combination of features related to sequence conservation, biophysical, and/or structural properties to link the observed variant to either neutral or disease phenotype. Despite notable successes, the mapping between genetic variants and their phenotypic effects is riddled with levels of complexity that are not yet fully understood and that are often not taken into account in the predictions, despite their promise of significantly improving the prediction of deleterious mutants. RESULTS: We present DEOGEN, a novel variant effect predictor that can handle both missense SNVs and in-frame INDELs. By integrating information from different biological scales and mimicking the complex mixture of effects that lead from the variant to the phenotype, we obtain significant improvements in the variant-effect prediction results. Next to the typical variant-oriented features based on the evolutionary conservation of the mutated positions, we added a collection of protein-oriented features that are based on functional aspects of the gene affected. We cross-validated DEOGEN on 36 825 polymorphisms, 20 821 deleterious SNVs, and 1038 INDELs from SwissProt. The multilevel contextualization of each (variant, protein) pair in DEOGEN provides a 10% improvement of MCC with respect to current state-of-the-art tools. AVAILABILITY AND IMPLEMENTATION: The software and the data presented here is publicly available at http://ibsquare.be/deogen CONTACT: : wvranken@vub.ac.be SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic profiling of primary and metastatic thyroid cancers.

The genetic repertoire of primary thyroid cancers (TCs) is well documented, but there is a considerable lack of molecular profiling in metastatic TCs. Here, we retrieved and analyzed the molecular and clinical features of 475 primary and metastatic TCs subjected to targeted DNA sequencing, from the cBioPortal database. The cohort included primary and metastatic samples from 276 papillary thyroid carcinomas (PTCs), 5 follicular thyroid carcinomas, 22 Hürthle cell carcinomas (HCCs), 127 poorly differentiated thyroid carcinomas (PDTCs), 30 anaplastic thyroid carcinomas (ATCs) and 15 medullary thyroid carcinomas. The ATCs had the highest tumor mutational burden and the HCCs the highest fraction of the genome altered. Compared to primary PTCs, the metastases had a significantly higher frequency of genetic alterations affecting TERT (51% vs 77%, P < 0.001), CDKN2A (2% vs 10%, P < 0.01), RET (2% vs 7%, P < 0.05), CDKN2B (1% vs 6%, P < 0.05) and BCOR (0% vs 4%, P < 0.05). The distant metastases had a significantly lower frequency of BRAF (64% vs 85%, P < 0.01) and a significantly higher frequency of NRAS (13% vs 3%, P < 0.05) hotspot mutations than the lymph node metastases. Metastases from HCCs and PDTCs were found to be enriched for NF1 (29%) and TP53 (18%) biallelic alterations, respectively. The frequency of subclonal mutations in ATCs was significantly higher than in PTCs (43% vs 25%, P < 0.01) and PDTCs (43% vs 22%, P < 0.01). Metastatic TCs are enriched in clinically informative genetic alterations such as RET translocations, BRAF hotspot mutations and NF1 biallelic losses that may be explored therapeutically.

Lynch Syndrome and Somatic Mismatch Repair Variants in Pancreas Cancer.

Importance: Microsatellite (MS) instability (MSI-H) occurs frequently in Lynch syndrome (LS)-associated tumors and is associated with response to immune checkpoint blockade (ICB) therapy. MSI-H is conferred by germline or somatic variants in mismatch repair genes. The contribution of somatic oncogenesis to MSI-H in pancreatic cancer (PC) is unknown. Objective: To evaluate an LS-related PC cohort to define clinicogenomic features, describe somatic MSI-H cases (germline negative), characterize response to ICB, and guide preferred MS testing methods. Design, Setting, and Participants: This single-institution, retrospective analysis was conducted from March 2012 to July 2023 at Memorial Sloan Kettering Cancer Center and included 55 patients with PC and either an LS germline pathogenic variant (gPV) or somatic mismatch repair (MMR) variant. Main Outcomes and Measures: Composite MMR and MS status determined using orthogonal methods. An artificial intelligence classifier was used to account for low-cellularity specimens. Demographic and clinical data were abstracted from medical record. Zygosity status and somatic comutation landscape analyzed. Results: Fifty-five patients (23 women [42%]) had PC and an MMR variant: 32 (58%) had LS (LS cohort) and 23 (42%) had a somatic MMR variant (no germline pathogenic variant, somatic MMR cohort). In the LS cohort, 10 (31%) had gMSH2, 9 (28%) gMSH6, 8 (25%) gPMS2, 4 (13%) gMLH1, 1 (3%) gEPCAM. The median age at diagnosis was 68 years (range, 45-88 years). For composite MS status, 17 (59%) were MSI-H, 12 (41%) MS stable, and 3 MS unknown. Five cases were reclassified as MSI-H by the artificial intelligence classifier. In the somatic MMR cohort, 11 (48%) had MSH6, 7 (30%) MLH1, 3 (13%) MSH2, and 2 (9%) PMS2. The median age at diagnosis was 72 years (range, 66-85 years). For composite MS status, 10 (43%) were MSI-H, 11 (48%) MS stable, and 2 (9%) MS indeterminate. Six cases were reclassified as MSI-H by the artificial intelligence classifier. For the LS and somatic MMR cohorts, 20 received ICB (n = 17 MSI-H). The median ICB duration was 27.7 months (95% CI, 11.5 to not reached); the disease control rate was 80%. Conclusion: The results of this cross-sectional study suggest that MSI-H occurs due to LS or somatic oncogenesis in PC. Orthogonal MS testing is key in PC; the artificial intelligence classifier reclassified approximately 20% of cases, most of which were low cellularity. ICB for patients with LS or somatic MSI-H PC provided significant benefit.

Large-scale copy number alterations are enriched for synthetic viability in BRCA1/BRCA2 tumors.

BACKGROUND: Pathogenic BRCA1 or BRCA2 germline mutations contribute to hereditary breast, ovarian, prostate, and pancreatic cancer. Paradoxically, bi-allelic inactivation of BRCA1 or BRCA2 (bBRCA1/2) is embryonically lethal and decreases cellular proliferation. The compensatory mechanisms that facilitate oncogenesis in bBRCA1/2 tumors remain unclear. METHODS: We identified recurrent genetic alterations enriched in human bBRCA1/2 tumors and experimentally validated if these improved proliferation in cellular models. We analyzed mutations and copy number alterations (CNAs) in bBRCA1/2 breast and ovarian cancer from the TCGA and ICGC. We used Fisher's exact test to identify CNAs enriched in bBRCA1/2 tumors compared to control tumors that lacked evidence of homologous recombination deficiency. Genes located in CNA regions enriched in bBRCA1/2 tumors were further screened by gene expression and their effects on proliferation in genome-wide CRISPR/Cas9 screens. A set of candidate genes was functionally validated with in vitro clonogenic survival and functional assays to validate their influence on proliferation in the setting of bBRCA1/2 mutations. RESULTS: We found that bBRCA1/2 tumors harbor recurrent large-scale genomic deletions significantly more frequently than histologically matched controls (n = 238 cytobands in breast and ovarian cancers). Within the deleted regions, we identified 277 BRCA1-related genes and 218 BRCA2-related genes that had reduced expression and increased proliferation in bBRCA1/2 but not in wild-type cells in genome-wide CRISPR screens. In vitro validation of 20 candidate genes with clonogenic proliferation assays validated 9 genes, including RIC8A and ATMIN (ATM-Interacting protein). We identified loss of RIC8A, which occurs frequently in both bBRCA1/2 tumors and is synthetically viable with loss of both BRCA1 and BRCA2. Furthermore, we found that metastatic homologous recombination deficient cancers acquire loss-of-function mutations in RIC8A. Lastly, we identified that RIC8A does not rescue homologous recombination deficiency but may influence mitosis in bBRCA1/2 tumors, potentially leading to increased micronuclei formation. CONCLUSIONS: This study provides a means to solve the tumor suppressor paradox by identifying synthetic viability interactions and causal driver genes affected by large-scale CNAs in human cancers.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer.

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

APOBEC3 mutagenesis drives therapy resistance in breast cancer.

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer 1-7 , however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

Genomic and epigenomic basis of breast invasive lobular carcinomas lacking CDH1 genetic alterations.

CDH1 (E-cadherin) bi-allelic inactivation is the hallmark alteration of breast invasive lobular carcinoma (ILC), resulting in its discohesive phenotype. A subset of ILCs, however, lack CDH1 genetic/epigenetic inactivation, and their genetic underpinning is unknown. Through clinical targeted sequencing data reanalysis of 364 primary ILCs, we identified 25 ILCs lacking CDH1 bi-allelic genetic alterations. CDH1 promoter methylation was frequent (63%) in these cases. Targeted sequencing reanalysis revealed 3 ILCs harboring AXIN2 deleterious fusions (n = 2) or loss-of-function mutation (n = 1). Whole-genome sequencing of 3 cases lacking bi-allelic CDH1 genetic/epigenetic inactivation confirmed the AXIN2 mutation and no other cell-cell adhesion genetic alterations but revealed a new CTNND1 (p120) deleterious fusion. AXIN2 knock-out in MCF7 cells resulted in lobular-like features, including increased cellular migration and resistance to anoikis. Taken together, ILCs lacking CDH1 genetic/epigenetic alterations are driven by inactivating alterations in other cell adhesion genes (CTNND1 or AXIN2), endorsing a convergent phenotype in ILC.

A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms.

Artificial intelligence (AI)-systems can improve cancer diagnosis, yet their development often relies on subjective histological features as ground truth for training. Here, we developed an AI-model applied to histological whole-slide images (WSIs) using CDH1 bi-allelic mutations, pathognomonic for invasive lobular carcinoma (ILC) in breast neoplasms, as ground truth. The model accurately predicted CDH1 bi-allelic mutations (accuracy=0.95) and diagnosed ILC (accuracy=0.96). A total of 74% of samples classified by the AI-model as having CDH1 bi-allelic mutations but lacking these alterations displayed alternative CDH1 inactivating mechanisms, including a deleterious CDH1 fusion gene and non-coding CDH1 genetic alterations. Analysis of internal and external validation cohorts demonstrated 0.95 and 0.89 accuracy for ILC diagnosis, respectively. The latent features of the AI-model correlated with human-explainable histopathologic features. Taken together, this study reports the construction of an AI-algorithm trained using a genetic rather than histologic ground truth that can robustly classify ILCs and uncover CDH1 inactivating mechanisms, providing the basis for orthogonal ground truth utilization for development of diagnostic AI-models applied to WSI.

Interferon response and epigenetic modulation by SMARCA4 mutations drive ovarian tumor immunogenicity.

Cell-intrinsic mechanisms of immunogenicity in ovarian cancer (OC) are not well understood. The presence of damaging mutations in the SWI/SNF chromatin remodeling complex, such as the SMARCA4 (BRG1) catalytic subunit, has been associated with improved response to ICB, however the mechanism by which this occurs is unclear. The aim of this current study was to examine the alterations in tumor cell-intrinsic and extrinsic immune signaling caused by SMARCA4 loss. Using OC models with loss-of-function mutations in SMARCA4 , we found that SMARCA4 loss resulted in increased cancer cell-intrinsic immunogenicity, characterized by upregulation of long-terminal RNA repeats such as endogenous retroviruses, increased expression of interferon-stimulated genes, and upregulation of antigen presentation machinery. Notably, this response was dependent on IRF3 signaling, but was independent of the type I interferon receptor. Mice inoculated with cancer cells bearing SMARCA4 loss demonstrated increased activation of cytotoxic T cells and NK cells in the tumor microenvironment as well as increased infiltration with activated dendritic cells. These results were recapitulated when animals bearing SMARCA4- proficient tumors were treated with a BRG1 inhibitor, suggesting that modulation of chromatin remodeling through targeting SMARCA4 may serve as a strategy to reverse immune evasion in OC.

KIT genetic alterations in breast cancer.

AIMS: Activating somatic mutations or gene amplification of KIT result in constitutive activation of its receptor tyrosine kinase, which is targetable in various solid tumours. Here, we sought to investigate the presence of KIT genetic alterations in breast cancer (BC) and characterise the histological and genomic features of these tumours. METHODS: A retrospective analysis of 5,575 BCs previously subjected to targeted sequencing using the FDA-authorised Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Targets (MSK-IMPACT) assay was performed to identify BCs with KIT alterations. A histological assessment of KIT-altered BCs was conducted, and their repertoire of genetic alterations was compared with that of BCs lacking KIT genetic alterations, matched for age, histological type, oestrogen receptor/HER2 status and sample type. RESULTS: We identified 18 BCs (0.32%), including 9 primary and 9 metastatic BCs, with oncogenic/likely oncogenic genetic alterations affecting KIT, including activating somatic mutations (n=4) or gene amplification (n=14). All KIT-altered BCs were of high histological grade, although no distinctive histological features were observed. When compared with BCs lacking KIT genetic alterations, no distinctive genetic features were identified. In two metastatic KIT-altered BCs in which the matched primary BC had also been analysed by MSK-IMPACT, the KIT mutations were found to be restricted to the metastatic samples, suggesting that they were late events in the evolution of these cancers. CONCLUSIONS: KIT genetic alterations are vanishingly rare in BC. KIT-altered BCs are of high grade but lack distinctive histological features. Genetic alterations in KIT might be late events in the evolution and/or progression of BC.

Clinicopathologic and genomic features of lobular like invasive mammary carcinoma: is it a distinct entity?

This study describes "lobular-like invasive mammary carcinomas" (LLIMCas), a group of low- to intermediate-grade invasive mammary carcinomas with discohesive, diffusely infiltrative cells showing retained circumferential membranous immunoreactivity for both E-cadherin and p120. We analyzed the clinical-pathologic features of 166 LLIMCas compared to 104 classical invasive lobular carcinomas (ILCs) and 100 grade 1 and 2 invasive ductal carcinomas (IDCs). Tumor size and pT stage of LLIMCas were intermediate between IDCs and ILCs, and yet often underestimated on imaging and showed frequent positive margins on the first resection. Despite histomorphologic similarities to classical ILC, the discohesion in LLIMCa was independent of E-cadherin/p120 immunophenotypic alteration. An exploratory, hypothesis-generating analysis of the genomic features of 14 randomly selected LLIMCas and classical ILCs (7 from each category) was performed utilizing an FDA-authorized targeted capture sequencing assay (MSK-IMPACT). None of the seven LLIMCas harbored CDH1 loss-of-function mutations, and none of the CDH1 alterations detected in two of the LLIMCas was pathogenic. In contrast, all seven ILCs harbored CDH1 loss-of-function mutations coupled with the loss of heterozygosity of the CDH1 wild-type allele. Four of the six evaluable LLIMCas were positive for CDH1 promoter methylation, which may partially explain the single-cell infiltrative morphology seen in LLIMCa. Further studies are warranted to better define the molecular basis of the discohesive cellular morphology in LLIMCa. Until more data becomes available, identifying LLIMCas and distinguishing them from typical IDCs and ILCs would be justified. In patients with LLIMCas, preoperative MRI should be entertained to guide surgical management.