Clonal expansion of intra-epithelial T cells in breast cancer revealed by spatial transcriptomics.

The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of tumor microenvironment. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse and more clonal than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top 10 dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

Response and Resistance to Trametinib in MAP2K1-Mutant Triple-Negative Melanoma.

The development of targeted therapies for non-BRAF p.Val600-mutant melanomas remains a challenge. Triple wildtype (TWT) melanomas that lack mutations in BRAF, NRAS, or NF1 form 10% of human melanomas and are heterogeneous in their genomic drivers. MAP2K1 mutations are enriched in BRAF-mutant melanoma and function as an innate or adaptive resistance mechanism to BRAF inhibition. Here we report the case of a patient with TWT melanoma with a bona fide MAP2K1 mutation without any BRAF mutations. We performed a structural analysis to validate that the MEK inhibitor trametinib could block this mutation. Although the patient initially responded to trametinib, he eventually progressed. The presence of a CDKN2A deletion prompted us to combine a CDK4/6 inhibitor, palbociclib, with trametinib but without clinical benefit. Genomic analysis at progression showed multiple novel copy number alterations. Our case illustrates the challenges of combining MEK1 and CDK4/6 inhibitors in case of resistance to MEK inhibitor monotherapy.

Activation of innate-adaptive immune machinery by poly(I:C) exposes a therapeutic vulnerability to prevent relapse in stroma-rich colon cancer.

OBJECTIVE: Stroma-rich tumours represent a poor prognostic subtype in stage II/III colon cancer (CC), with high relapse rates and limited response to standard adjuvant chemotherapy. DESIGN: To address the lack of efficacious therapeutic options for patients with stroma-rich CC, we stratified our human tumour cohorts according to stromal content, enabling identification of the biology underpinning relapse and potential therapeutic vulnerabilities specifically within stroma-rich tumours that could be exploited clinically. Following human tumour-based discovery and independent clinical validation, we use a series of in vitro and stroma-rich in vivo models to test and validate the therapeutic potential of elevating the biology associated with reduced relapse in human tumours. RESULTS: By performing our analyses specifically within the stroma-rich/high-fibroblast (HiFi) subtype of CC, we identify and validate the clinical value of a HiFi-specific prognostic signature (HPS), which stratifies tumours based on STAT1-related signalling (High-HPS v Low-HPS=HR 0.093, CI 0.019 to 0.466). Using in silico, in vitro and in vivo models, we demonstrate that the HPS is associated with antigen processing and presentation within discrete immune lineages in stroma-rich CC, downstream of double-stranded RNA and viral response signalling. Treatment with the TLR3 agonist poly(I:C) elevated the HPS signalling and antigen processing phenotype across in vitro and in vivo models. In an in vivo model of stroma-rich CC, poly(I:C) treatment significantly increased systemic cytotoxic T cell activity (p<0.05) and reduced liver metastases (p<0.0002). CONCLUSION: This study reveals new biological insight that offers a novel therapeutic option to reduce relapse rates in patients with the worst prognosis CC.

Citizens' views on sharing their health data: the role of competence, reliability and pursuing the common good.

BACKGROUND: In this article, we address questions regarding how people consider what they do or do not consent to and the reasons why. This article presents the findings of a citizen forum study conducted by the University of Geneva in partnership with the Geneva University Hospitals to explore the opinions and concerns of members of the public regarding predictive oncology, genetic sequencing, and cancer. METHODS: This paper presents the results of a citizen forum that included 73 participants. A research tool titled "the mechanics of consent" was designed for this study. This tool is a table encouraging participants to reflect on social and research actors, types of data, and desired levels of control while sharing different types of data with different actors. Participants' discussion that led to the completion of each table were audio-recorded, transcribed, and analyzed using thematic analysis. RESULTS: The results are a compilation of responses from the mechanics of consent tool divided into two sections; the first presents quantitative results of collective responses regarding attitudes to consent to donate their data. The second section present qualitative findings emerged from the discussion amongst participants. DISCUSSION: Choice and control of personal data is crucial for the public to be able to decide who and how to trust. Key information to be disclosed to potential research participants shall include information about potential risks and benefits; who will be accessing and using their data; as well as assurances that their choice will be respected. Furthermore, researchers ought to make sure they are trustworthy, by acting in a competent, reliable, and honest manner. Governance systems ought to be better equipped to address ethical issues raise by the growing presence of non-traditional research actors, consent of exchanges of data via digital devices and online activity such as social media and fairness of data trading. Finally, informed consent is one of the various elements that contribute to conducting ethical research. More needs to be done to strengthen governance and ensure adequate protection of research participants, particularly to address issues related to predictive health analytics.

Primordial germ cells as a potential shared cell of origin for mucinous cystic neoplasms of the pancreas and mucinous ovarian tumors.

Mucinous ovarian tumors (MOTs) morphologically and epidemiologically resemble mucinous cystic neoplasms (MCNs) of the pancreas, sharing a similar stroma and both occurring disproportionately among young females. Additionally, MOTs and MCNs share similar clinical characteristics and immunohistochemical phenotypes. Exome sequencing has revealed frequent recurrent mutations in KRAS and RNF43 in both MOTs and MCNs. The cell of origin for these tumors remains unclear, but MOTs sometimes arise in the context of mature cystic teratomas and other primordial germ cell (PGC) tumors. We undertook the present study to investigate whether non-teratoma-associated MOTs and MCNs share a common cell of origin. Comparisons of the gene expression profiles of MOTs [including both the mucinous borderline ovarian tumors (MBOTs) and invasive mucinous ovarian carcinomas (MOCs)], high-grade serous ovarian carcinomas, ovarian surface epithelium, Fallopian tube epithelium, normal pancreatic tissue, pancreatic duct adenocarcinomas, MCNs, and single-cell RNA-sequencing of PGCs revealed that both MOTs and MCNs are more closely related to PGCs than to either eutopic epithelial tumors or normal epithelia. We hypothesize that MCNs may arise from PGCs that stopped in the dorsal pancreas during their descent to the gonads during early human embryogenesis, while MOTs arise from PGCs in the ovary. Together, these data suggest a common pathway for the development of MCNs and MOTs, and suggest that these tumors may be more properly classified as germ cell tumor variants. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Report on the first SLFN11 monothematic workshop: from function to role as a biomarker in cancer.

SLFN11 is a recently discovered protein with a putative DNA/RNA helicase function. First identified in association with the maturation of thymocytes, SLFN11 was later causally associated, by two independent groups, with the resistance to DNA damaging agents such as topoisomerase I and II inhibitors, platinum compounds, and other alkylators, making it an attractive molecule for biomarker development. Later, SLFN11 was linked to antiviral response in human cells and interferon production, establishing a potential bond between immunity and chemotherapy. Recently, we demonstrated the potential role of SLN11 as a biomarker to predict sensitivity to the carboplatin/taxol combination in ovarian cancer. The present manuscript reports on the first international monothematic workshop on SLFN11. Several researchers from around the world, directly and actively involved in the discovery, functional characterization, and study of SLFN11 for its biomarker and medicinal properties gathered to share their views on the current knowledge advances concerning SLFN11. The aim of the manuscript is to summarize the authors' interventions and the main take-home messages resulting from the workshop.

[Follow-up of the long-term cancer survivor]. / Suivi à long terme du patient oncologique : enjeux et défis.

Improvements in diagnosis and treatments explain the notable increase in patients chronically affected or recovering from cancer. This is a fragile population, who is physically, psychologically and socially affected by the consequences of the disease and the associated treatments. In addition to detecting a possible relapse, oncologists and primary care physicians have to deal with a variety of issues like psychological distress, sexual dysfunction, cardiotoxicity, cognitive impairment, fatigue and, in some cases, a second primary cancer. This is a real challenge for modern medical oncology, with an important financial impact. A long-term structured follow-up could improve the management of patients with a history of cancer and favour their physical recovery and psychosocial integration.

Les progrès accomplis dans le diagnostic et le traitement oncologique sont à l'origine d'une augmentation remarquable du nombre de patients guéris ou souffrant chroniquement d'un cancer. Il s'agit d'une population touchée sur le plan physique, psychologique et socio-économique par les effets de la maladie et du traitement reçu. Au-delà de la détection de la récidive, l'oncologue et le généraliste seront confrontés à la gestion de problématiques telles que la détresse psychologique, la cardiotoxicité, les troubles cognitifs, la fatigue ou l'apparition d'un deuxième cancer primaire. Il s'agit d'un véritable défi de l'oncologie moderne, dont l'impact économique sera majeur. Un suivi à long terme structuré pourrait améliorer la prise en charge de ces patients et favoriser leur récupération physique et leur intégration psychosociale.

Mutational analysis of anal cancers demonstrates frequent PIK3CA mutations associated with poor outcome after salvage abdominoperineal resection.

BACKGROUND: A better understanding of the molecular profile of anal squamous cell carcinomas (ASCCs) is necessary to consider new therapeutic approaches, and the identification of prognostic and predictive factors for response to treatment. METHODS: We retrospectively analysed tumours from ASCC patients for mutational analysis of KRAS, NRAS, HRAS, BRAF, PIK3CA, MET, TP53 and FBXW7 genes by HRM and Sanger sequencing analysis. RESULTS: Specimens from 148 patients were analysed: 96 treatment-naive tumours and 52 recurrences after initial radiotherapy (RT) or chemoradiotherapy (CRT). Mutations of KRAS, PIK3CA, FBXW7 and TP53 genes were present in 3 (2.0%), 30 (20.3%), 9 (6.1%) and 7 tumours (4.7%), respectively. The distribution of the mutations was similar between treatment-naive tumours and recurrences, except for TP53 mutations being more frequent in recurrences (P=0.0005). In patients treated with abdominoperineal resection (APR) after relapse (n=38, median follow-up of 18.2 years), overall survival (OS) was significantly correlated with HPV16 status (P=0.048), gender (P=0.045) and PIK3CA mutation (P=0.037). The PIK3CA status retained its prognostic significance in Cox multivariate regression analysis (P=0.025). CONCLUSIONS: Our study identified PIK3CA mutation as an independent prognostic factor in patients who underwent APR for ASCC recurrence, suggesting a potential benefit from adjuvant treatment and the evaluation of targeted therapies with PI3K/Akt/mTor inhibitors in PIK3CA-mutated patients.

[Bioinformatics: a key role in oncology]. / Bioinformatique en oncologie: une discipline incontournable.

Bioinformatics is essential in clinical oncology and research. Combining biology, computer science and mathematics, bioinformatics aims to derive useful information from clinical and biological data, often poorly structured, at a large scale. Bioinformatics approaches have reclassified certain cancers based on their molecular and biological presentation, improving treatment selection. Many molecular signatures have been developed and, after validation, some are now usable in clinical practice. Other applications could facilitate daily practice, reduce the risk of error and increase the precision of medical decision-making. Bioinformatics must evolve in accordance with ethical considerations and requires multidisciplinary collaboration. Its application depends on a sound technical foundation that meets strict quality requirements.

Are common fragile sites merely structural domains or highly organized "functional" units susceptible to oncogenic stress?

Common fragile sites (CFSs) are regions of the genome with a predisposition to DNA double-strand breaks in response to intrinsic (oncogenic) or extrinsic replication stress. CFS breakage is a common feature in carcinogenesis from its earliest stages. Given that a number of oncogenes and tumor suppressors are located within CFSs, a question that emerges is whether fragility in these regions is only a structural "passive" incident or an event with a profound biological effect. Furthermore, there is sparse evidence that other elements, like non-coding RNAs, are positioned with them. By analyzing data from various libraries, like miRbase and ENCODE, we show a prevalence of various cancer-related genes, miRNAs, and regulatory binding sites, such as CTCF within CFSs. We propose that CFSs are not only susceptible structural domains, but highly organized "functional" entities that when targeted, severe repercussion for cell homeostasis occurs.

Development and Validation of an Inflammatory Prognostic Index to Predict Outcomes in Advanced/Metastatic Urothelial Cancer Patients Receiving Immune Checkpoint Inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) improve overall survival (OS) in advanced/metastatic urothelial cancer (a/mUC) patients. Preliminary evidence suggests a prognostic role of inflammatory biomarkers in this setting. We aimed to develop a disease-specific prognostic inflammatory index for a/mUC patients on ICIs. METHODS: Fifteen variables were retrospectively correlated with OS and progression-free survival (PFS) in a development (D, n = 264) and a validation (V, n = 132) cohort of platinum-pretreated a/mUC pts receiving ICIs at L2 or further line. A nomogram and inflammatory prognostic index (U-IPI) were developed. The index was also tested in a control cohort of patients treated with chemotherapy only (C, n = 114). RESULTS: The strongest predictors of OS were baseline platelet/lymphocyte (PLR) and neutrophil/lymphocyte (NLR) ratios, and lactate dehydrogenase (LDH), NLR, and albumin changes at 4 weeks. These were used to build the U-IPI, which can distinctly classify patients into good or poor response groups. The nomogram scoring is significant for PFS and OS (p < 0.001 in the D, V, and combined cohorts) for the immunotherapy (IO) cohort, but not for the control cohort. CONCLUSIONS: The lack of a baseline systemic inflammatory profile and the absence of early serum inflammatory biomarker changes are associated with significantly better outcomes on ICIs in a/mUC pts. The U-IPI is an easily applicable dynamic prognostic tool for PFS and OS, allowing for the early identification of a sub-group with dismal outcomes that would not benefit from ICIs, while distinguishing another that draws an important benefit.

Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer.

Molecular stratification using gene-level transcriptional data has identified subtypes with distinctive genotypic and phenotypic traits, as exemplified by the consensus molecular subtypes (CMS) in colorectal cancer (CRC). Here, rather than gene-level data, we make use of gene ontology and biological activation state information for initial molecular class discovery. In doing so, we defined three pathway-derived subtypes (PDS) in CRC: PDS1 tumors, which are canonical/LGR5+ stem-rich, highly proliferative and display good prognosis; PDS2 tumors, which are regenerative/ANXA1+ stem-rich, with elevated stromal and immune tumor microenvironmental lineages; and PDS3 tumors, which represent a previously overlooked slow-cycling subset of tumors within CMS2 with reduced stem populations and increased differentiated lineages, particularly enterocytes and enteroendocrine cells, yet display the worst prognosis in locally advanced disease. These PDS3 phenotypic traits are evident across numerous bulk and single-cell datasets, and demark a series of subtle biological states that are currently under-represented in pre-clinical models and are not identified using existing subtyping classifiers.

Immunotherapy in Urological, Gynecological and Gastrointestinal Cancers - Current Landscape.

Immunotherapy is becoming increasingly important in the management of urological, gynecological, and gastrointestinal cancers. Immune checkpoint inhibitor-based combinations have become a standard of care for patients with metastatic renal and liver cancers, as well as for many patients with bladder, cervical, gastric, and esophageal cancers, based on various biomarkers. Some tumor types are less responsive to immunotherapy, such as prostate and colon cancer. In these tumors, however, a subgroup of patients with a microsatellite-instability-high/DNA-mismatch repair deficient molecular phenotype significantly benefits from immunotherapy. Molecular characterization is therefore essential to identify patients who may benefit from these treatments. One of the major challenges is the search for new predictive biomarkers and novel combinations or strategies to further improve patient outcome.

Characteristics of long-survivor metastatic melanoma after polychemotherapy and interferon: a retrospective study.

BACKGROUND: The development of immunotherapy and tyrosine kinase inhibitors dramatically improved the prognosis of metastatic melanoma. Consequently, chemotherapy is now rarely used. Here, we describe the characteristics of long-surviving patients with metastatic melanoma treated with immunochemotherapy. MATERIAL AND METHODS: We retrieved retrospective clinical and pathological data for patients diagnosed with metastatic melanoma between January 1993 and December 2015 who received the CVD-INF (cisplatin, vinblastine, dacarbazine, and interferon α-2b) regimen at the Hôpitaux Universitaires de Genève. We estimated their progression-free survival and overall survival. This ad hoc study's primary aim was to describe the clinical and biological characteristics of long-term survivors, defined as patients surviving more than two years after immunochemotherapy initiation. The spatial distribution pattern of CD8+ T cells (inflamed, excluded, or desert) was immunohistochemically determined. RESULTS: Ninety patients received CVD-INF. Their median age at metastatic melanoma diagnosis was 55 years (20-75). Their median progression-free survival was 2.8 months, and median overall survival was 7.2 months. Eleven (12%) patients were long-term survivors. In multivariate analysis, central nervous system metastases (hazard ratio [HR]: 2.66; 95% confidence interval [CI]: 1.43-4.95; p = 0.001), multiple metastases (HR: 1.82; 95% CI: 1.01-3.29; p = 0.047), and elevated lactate dehydrogenase (LDH) (HR: 1.92; 95% CI: 1.12-3.30; p = 0.016) were independently associated with shorter survival. Most long-survivors (6/8; 75%) had a tumour-inflamed pattern compared to 25% of non-long survivors (5/20; Fisher's test p = 0.030). CONCLUSIONS: A subset of patients with metastatic melanoma and a tumour-inflamed phenotype treated with CVD-INF survived over two years. Factors associated with prolonged survival are consistent with those previously reported in metastatic melanoma.

The first comprehensive genomic characterization of rectal squamous cell carcinoma.

BACKGROUND: Rectal cancers represent 35% of colorectal cancers; 90% are adenocarcinomas, while squamous cell carcinoma accounts for 0.3% of them. Given its rarity, little is known concerning its pathogenesis, molecular profile and therapeutic management. The current treatment trend is to treat rectal squamous cell carcinoma by analogy to anal squamous cell carcinoma with definitive chemo-radiotherapy, setting aside surgery in case of local recurrence. METHODS: We performed an in-depth genomic analysis (next-generation sequencing, copy number variation, and human papilloma virus characterization) on 10 rectal squamous cell carcinoma samples and compared them in silico to those of anal squamous cell carcinoma and rectal adenocarcinoma. RESULTS: Rectal squamous cell carcinoma shows 100% HPV positivity. It has a mutational (PIK3CA, PTEN, TP53, ATM, BCL6, SOX2) and copy number variation profile (3p, 10p, 10q, 16q deletion and 1q, 3q, 5p, 8q, 20p gain) similar to anal squamous cell carcinoma. PI3K/Akt/mTOR is the most commonly affected signaling pathway similarly to anal squamous cell carcinoma. Most commonly gained or lost genes seen in rectal adenocarcinoma (FLT3, CDX2, GNAS, BCL2, SMAD4, MALT1) are not found in rectal squamous cell carcinoma. CONCLUSION: This study presents the first comprehensive genomic characterization of rectal squamous cell carcinoma. We confirm the existence of this rare histology and its molecular similarity with anal squamous cell carcinoma. This molecular proximity confirms the adequacy of therapeutic management based on histology and not localization, suggesting that rectal squamous cell carcinoma should be treated like anal squamous cell carcinoma and not as a rectal adenocarcinoma.

Multilingual RECIST classification of radiology reports using supervised learning.

Objectives: The objective of this study is the exploration of Artificial Intelligence and Natural Language Processing techniques to support the automatic assignment of the four Response Evaluation Criteria in Solid Tumors (RECIST) scales based on radiology reports. We also aim at evaluating how languages and institutional specificities of Swiss teaching hospitals are likely to affect the quality of the classification in French and German languages. Methods: In our approach, 7 machine learning methods were evaluated to establish a strong baseline. Then, robust models were built, fine-tuned according to the language (French and German), and compared with the expert annotation. Results: The best strategies yield average F1-scores of 90% and 86% respectively for the 2-classes (Progressive/Non-progressive) and the 4-classes (Progressive Disease, Stable Disease, Partial Response, Complete Response) RECIST classification tasks. Conclusions: These results are competitive with the manual labeling as measured by Matthew's correlation coefficient and Cohen's Kappa (79% and 76%). On this basis, we confirm the capacity of specific models to generalize on new unseen data and we assess the impact of using Pre-trained Language Models (PLMs) on the accuracy of the classifiers.

Interdisciplinary Swiss consensus recommendations on staging and treatment of advanced prostate cancer.

The management of prostate cancer is undergoing rapid changes in all disease settings. Novel imaging tools for diagnosis have been introduced, and the treatment of high-risk localized, locally advanced and metastatic disease has changed considerably in recent years. From clinical and health-economic perspectives, a rational and optimal use of the available options is of the utmost importance. While international guidelines list relevant pivotal trials and give recommendations for a variety of clinical scenarios, there is much room for interpretation, and several important questions remain highly debated. The goal of developing a national consensus on the use of these novel diagnostic and therapeutic strategies in order to improve disease management and eventually patient outcomes has prompted a Swiss consensus meeting. Experts from several specialties, including urology, medical oncology, radiation oncology, pathology and nuclear medicine, discussed and voted on questions of the current most important areas of uncertainty, including the staging and treatment of high-risk localized disease, treatment of metastatic hormone-sensitive prostate cancer (mHSPC) and use of new options to treat metastatic castration-resistant prostate cancer (mCRPC).

The Landscape of Immunotherapy Resistance in NSCLC.

Lung cancer is the leading cause of cancer mortality worldwide. Immunotherapy has demonstrated clinically significant benefit for non-small-cell lung cancer, but innate (primary) or acquired resistance remains a challenge. Criteria for a uniform clinical definition of acquired resistance have been recently proposed in order to harmonize the design of future clinical trials. Several mechanisms of resistance are now well-described, including the lack of tumor antigens, defective antigen presentation, modulation of critical cellular pathways, epigenetic changes, and changes in the tumor microenvironment. Host-related factors, such as the microbiome and the state of immunity, have also been examined. New compounds and treatment strategies are being developed to target these mechanisms with the goal of maximizing the benefit derived from immunotherapy. Here we review the definitions of resistance to immunotherapy, examine its underlying mechanisms and potential corresponding treatment strategies. We focus on recently published clinical trials and trials that are expected to deliver results soon. Finally, we gather insights from recent preclinical discoveries that may translate to clinical application in the future.

Structure-based prediction of BRAF mutation classes using machine-learning approaches.

The BRAF kinase is attracting a lot of attention in oncology as alterations of its amino acid sequence can constitutively activate the MAP kinase signaling pathway, potentially contributing to the malignant transformation of the cell but at the same time rendering it sensitive to targeted therapy. Several pathologic BRAF variants were grouped in three different classes (I, II and III) based on their effects on the protein activity and pathway. Discerning the class of a BRAF mutation permits to adapt the treatment proposed to the patient. However, this information is lacking new and experimentally uncharacterized BRAF mutations detected in a patient biopsy. To overcome this issue, we developed a new in silico tool based on machine learning approaches to predict the potential class of a BRAF missense variant. As class I only involves missense mutations of Val600, we focused on the mutations of classes II and III, which are more diverse and challenging to predict. Using a logistic regression model and features including structural information, we were able to predict the classes of known mutations with an accuracy of 90%. This new and fast predictive tool will help oncologists to tackle potential pathogenic BRAF mutations and to propose the most appropriate treatment for their patients.