Protease activated receptor (PAR)-1 expression is increased in a variety of tumor cells. In preclinical models, tumor cell PAR-1 appeared to be involved in the regulation of lung tumor growth and metastasis; however the role of PAR-1 in the lung tumor microenvironment, which is emerging as a key compartment in driving cancer progression, remained to be explored.

Adult-type granulosa cell tumors (AGCTs) are sex-cord derived neoplasms with a propensity for late relapse. Hormonal modulators have been used empirically in the treatment of recurrent AGCT, albeit with limited success. To provide a more rigorous foundation for hormonal therapy in AGCT, we used a multimodal approach to characterize the expressions of key hormone biomarkers in 175 tumor specimens and 51 serum samples using RNA sequencing, immunohistochemistry, RNA in situ hybridization, quantitative PCR, and circulating biomarker analysis, and correlated these results with clinical data. We show that FSH receptor and estrogen receptor beta (ERβ) are highly expressed in the majority of AGCTs, whereas the expressions of estrogen receptor alpha (ERα) and G-protein coupled estrogen receptor 1 are less prominent. ERβ protein expression is further increased in recurrent tumors. Aromatase expression levels show high variability between tumors. None of the markers examined served as prognostic biomarkers for progression-free or overall survival. In functional experiments, we assessed the effects of FSH, estradiol (E2), and the aromatase inhibitor letrozole on AGCT cell viability using 2 in vitro models: KGN cells and primary cultures of AGCT cells. FSH increased cell viability in a subset of primary AGCT cells, whereas E2 had no effect on cell viability at physiological concentrations. Letrozole suppressed E2 production in AGCTs; however, it did not impact cell viability. We did not find preclinical evidence to support the clinical use of aromatase inhibitors in AGCT treatment, and thus randomized, prospective clinical studies are needed to clarify the role of hormonal treatments in AGCTs.

Melanomas can switch to a dedifferentiated cell state upon exposure to cytotoxic T cells. However, it is unclear whether such tumor cells pre-exist in patients and whether they can be resensitized to immunotherapy. Here, we chronically expose (patient-derived) melanoma cell lines to differentiation antigen-specific cytotoxic T cells and observe strong enrichment of a pre-existing NGFRhi population. These fractions are refractory also to T cells recognizing non-differentiation antigens, as well as to BRAF + MEK inhibitors. NGFRhi cells induce the neurotrophic factor BDNF, which contributes to T cell resistance, as does NGFR. In melanoma patients, a tumor-intrinsic NGFR signature predicts anti-PD-1 therapy resistance, and NGFRhi tumor fractions are associated with immune exclusion. Lastly, pharmacologic NGFR inhibition restores tumor sensitivity to T cell attack in vitro and in melanoma xenografts. These findings demonstrate the existence of a stable and pre-existing NGFRhi multitherapy-refractory melanoma subpopulation, which ought to be eliminated to revert intrinsic resistance to immunotherapeutic intervention.

Adult-type granulosa cell tumors (aGCTs) account for 90% of malignant ovarian sex cord-stromal tumors and 2-5% of all ovarian cancers. These tumors are usually diagnosed at an early stage and are treated with surgery. However, one-third of patients relapse between 4 and 8 years after initial diagnosis, and there are currently no effective treatments other than surgery for these relapsed patients. As the majority of aGCTs (>95%) harbor a somatic mutation in FOXL2 (c.C402G; p.C134W), the aim of this study was to identify genetic mutations besides FOXL2 C402G in aGCTs that could explain the clinical diversity of this disease. Whole-genome sequencing of 10 aGCTs and their matched normal blood was performed to identify somatic mutations. From this analysis, a custom amplicon-based panel was designed to sequence 39 genes of interest in a validation cohort of 83 aGCTs collected internationally. KMT2D inactivating mutations were present in 10 of 93 aGCTs (10.8%), and the frequency of these mutations was similar between primary and recurrent aGCTs. Inactivating mutations, including a splice site mutation in candidate tumor suppressor WNK2 and nonsense mutations in PIK3R1 and NLRC5, were identified at a low frequency in our cohort. Missense mutations were identified in cell cycle-related genes TP53, CDKN2D, and CDK1. From these data, we conclude that aGCTs are comparatively a homogeneous group of tumors that arise from a limited set of genetic events and are characterized by the FOXL2 C402G mutation. Secondary mutations occur in a subset of patients but do not explain the diverse clinical behavior of this disease. As the FOXL2 C402G mutation remains the main driver of this disease, progress in the development of therapeutics for aGCT would likely come from understanding the functional consequences of the FOXL2 C402G mutation.

Basal-like breast cancers (BLBC) are aggressive breast cancers for which, so far, no targeted therapy is available because they typically lack expression of hormone receptors and HER2. Phenotypic features of BLBCs, such as clinical presentation and early age of onset, resemble those of breast tumors from BRCA1-mutation carriers. The genomic instability of BRCA1-mutated tumors can be effectively targeted with DNA-damaging agents and poly-(ADP-ribose) polymerase 1 (PARP1) inhibitors. Molecular similarities between BLBCs and BRCA1-mutated tumors may therefore provide predictive markers for therapeutic response of BLBCs.

Adjuvant! Online is a web-based application designed to provide 10 years survival probability of patients with breast cancer. Several predictors have not been assessed in the original Adjuvant! Online study. We provide the validation of Adjuvant! Online algorithm on two breast cancer datasets, and we determined whether the accuracy of Adjuvant! Online is improved with other well-known prognostic factors.

The basal-like breast cancer (BLBC) subtype is characterized by positive staining for basal mammary epithelial cytokeratin markers, lack of hormone receptor and HER2 expression, and poor prognosis with currently no approved molecularly-targeted therapies. The oncogenic signaling pathways driving basal-like tumorigenesis are not fully elucidated.

The clinical benefit for patients with diverse types of metastatic cancers that has been observed upon blockade of the interaction between PD-1 and PD-L1 has highlighted the importance of this inhibitory axis in the suppression of tumour-specific T-cell responses. Notwithstanding the key role of PD-L1 expression by cells within the tumour micro-environment, our understanding of the regulation of the PD-L1 protein is limited. Here we identify, using a haploid genetic screen, CMTM6, a type-3 transmembrane protein of previously unknown function, as a regulator of the PD-L1 protein. Interference with CMTM6 expression results in impaired PD-L1 protein expression in all human tumour cell types tested and in primary human dendritic cells. Furthermore, through both a haploid genetic modifier screen in CMTM6-deficient cells and genetic complementation experiments, we demonstrate that this function is shared by its closest family member, CMTM4, but not by any of the other CMTM members tested. Notably, CMTM6 increases the PD-L1 protein pool without affecting PD-L1 (also known as CD274) transcription levels. Rather, we demonstrate that CMTM6 is present at the cell surface, associates with the PD-L1 protein, reduces its ubiquitination and increases PD-L1 protein half-life. Consistent with its role in PD-L1 protein regulation, CMTM6 enhances the ability of PD-L1-expressing tumour cells to inhibit T cells. Collectively, our data reveal that PD-L1 relies on CMTM6/4 to efficiently carry out its inhibitory function, and suggest potential new avenues to block this pathway.

Autophagy, a lysosome-mediated degradation and recycling process, functions in advanced malignancies to promote cancer cell survival and contribute to cancer progression and drug resistance. While various autophagy inhibition strategies are under investigation for cancer treatment, corresponding patient selection criteria for these autophagy inhibitors need to be developed. Due to its central roles in the autophagy process, the cysteine protease ATG4B is one of the autophagy proteins being pursued as a potential therapeutic target. In this study, we investigated the expression of ATG4B in breast cancer, a heterogeneous disease comprised of several molecular subtypes. We examined a panel of breast cancer cell lines, xenograft tumors, and breast cancer patient specimens for the protein expression of ATG4B, and found a positive association between HER2 and ATG4B protein expression. We showed that HER2-positive cells, but not HER2-negative breast cancer cells, require ATG4B to survive under stress. In HER2-positive cells, cytoprotective autophagy was dependent on ATG4B under both starvation and HER2 inhibition conditions. Combined knockdown of ATG4B and HER2 by siRNA resulted in a significant decrease in cell viability, and the combination of ATG4B knockdown with trastuzumab resulted in a greater reduction in cell viability compared to trastuzumab treatment alone, in both trastuzumab-sensitive and -resistant HER2 overexpressing breast cancer cells. Together these results demonstrate a novel association of ATG4B positive expression with HER2 positive breast cancers and indicate that this subtype is suitable for emerging ATG4B inhibition strategies.

We present a novel hierarchical Bayes statistical model, xseq, to systematically quantify the impact of somatic mutations on expression profiles. We establish the theoretical framework and robust inference characteristics of the method using computational benchmarking. We then use xseq to analyse thousands of tumour data sets available through The Cancer Genome Atlas, to systematically quantify somatic mutations impacting expression profiles. We identify 30 novel cis-effect tumour suppressor gene candidates, enriched in loss-of-function mutations and biallelic inactivation. Analysis of trans-effects of mutations and copy number alterations with xseq identifies mutations in 150 genes impacting expression networks, with 89 novel predictions. We reveal two important novel characteristics of mutation impact on expression: (1) patients harbouring known driver mutations exhibit different downstream gene expression consequences; (2) expression patterns for some mutations are stable across tumour types. These results have critical implications for identification and interpretation of mutations with consequent impact on transcription in cancer.

The 19q12 locus is amplified in a subgroup of oestrogen receptor (ER)-negative grade III breast cancers. This amplicon comprises nine genes, including cyclin E1 (CCNE1), which has been proposed as its 'driver'. The aim of this study was to identify the genes within the 19q12 amplicon whose expression is required for the survival of cancer cells harbouring their amplification.

Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.

Resistance to platinum-based chemotherapy represents a major clinical challenge for many tumors, including epithelial ovarian cancer. Patients often experience several response-relapse events, until tumors become resistant and life expectancy drops to 12-15 months. Despite improved knowledge of the molecular determinants of platinum resistance, the lack of clinical applicability limits exploitation of many potential targets, leaving patients with limited options. Serine biosynthesis has been linked to cancer growth and poor prognosis in various cancer types, however its role in platinum-resistant ovarian cancer is not known. Here, we show that a subgroup of resistant tumors decreases phosphoglycerate dehydrogenase (PHGDH) expression at relapse after platinum-based chemotherapy. Mechanistically, we observe that this phenomenon is accompanied by a specific oxidized nicotinamide adenine dinucleotide (NAD+) regenerating phenotype, which helps tumor cells in sustaining Poly (ADP-ribose) polymerase (PARP) activity under platinum treatment. Our findings reveal metabolic vulnerabilities with clinical implications for a subset of platinum resistant ovarian cancers.

Immune checkpoint blockade (ICB) is currently approved for patients with triple-negative breast cancer (TNBC), whereas responses to ICB are also observed in a small subgroup of Estrogen Receptor (ER)-positive breast cancer. The cut-off for ER-positivity (≥1%) is based on likelihood of endocrine treatment response, but ER-positive breast cancer represents a very heterogeneous group. This raises the question whether selection based on ER-negativity should be revisited to select patients for ICB treatment in the context of clinical trials. Stromal tumor-infiltrating lymphocytes (sTILs) and other immune parameters are higher in TNBC compared to ER-positive breast cancer, but it is unknown whether lower ER levels are associated with more inflamed tumor microenvironments (TME). We collected a consecutive series of primary tumors from 173 HER2-negative breast cancer patients, enriched for tumors with ER expression between 1 and 99% and found levels of stromal TILs, CD8 + T cells, and PD-L1 positivity in breast tumors with ER 1-9% and ER 10-50% to be comparable to tumors with ER 0%. Expression of immune-related gene signatures in tumors with ER 1-9% and ER 10-50% was comparable to ER 0%, and higher than in tumors with ER 51-99% and ER 100%. Our results suggest that the immune landscape of ER low tumors (1-9%) and ER intermediate tumors (10-50%) mimic that of primary TNBC.

Digital health data used in diagnostics, patient care, and oncology research continue to accumulate exponentially. Most medical information, and particularly radiology results, are stored in free-text format, and the potential of these data remains untapped. In this study, a radiological repomics-driven model incorporating medical token cognition (RadioLOGIC) is proposed to extract repomics (report omics) features from unstructured electronic health records and to assess human health and predict pathological outcome via transfer learning. The average accuracy and F1-weighted score for the extraction of repomics features using RadioLOGIC are 0.934 and 0.934, respectively, and 0.906 and 0.903 for the prediction of breast imaging-reporting and data system scores. The areas under the receiver operating characteristic curve for the prediction of pathological outcome without and with transfer learning are 0.912 and 0.945, respectively. RadioLOGIC outperforms cohort models in the capability to extract features and also reveals promise for checking clinical diagnoses directly from electronic health records.

Despite major improvements in treatment of HER2-positive metastatic breast cancer (MBC), only few patients achieve complete remission and remain progression free for a prolonged time. The tumor immune microenvironment plays an important role in the response to treatment in HER2-positive breast cancer and could contain valuable prognostic information. Detailed information on the cancer-immune cell interactions in HER2-positive MBC is however still lacking. By characterizing the tumor immune microenvironment in patients with HER2-positive MBC, we aimed to get a better understanding why overall survival (OS) differs so widely and which alternative treatment approaches may improve outcome.

Among breast cancer patients who develop distant metastases, there is marked variability in the clinical course, including metastasis pattern. Here, we present a retrospective study of breast cancer patients who all developed distant metastases focusing on the association between breast cancer subtype and clinical course, including organ-specific metastasis. Tissue microarrays (TMAs) were assembled and stained for ER, PR, HER2, EGFR, CK5/6, CK14, E-Cadherin, TP53 and Ki67 for 263 breast cancer patients with metastatic disease. Tumours were classified into ER+/HER2-/Ki67high, ER+/HER2-/Ki67low, ER+/HER2+, ER-/HER2+ and ER-/HER2- groups. Relevant data related to metastasis pattern, metastasis timeline, systemic treatment and survival were retrieved. Associations between site-specific relapse and patient/tumour characteristics were assessed with multivariate models using logistic regression. Median time for development of distant metastasis was 30 months (range 0-15.3 years); 75.8 % of the distance metastases developed in the first 5 years after treatment of the primary tumour. Patients with ER-/HER2- tumours had a median overall survival of 27 months; those with HER2+ tumours of 52 months; those with ER+/HER2-/Ki67high of 76 months and those with ER+/HER2-/Ki67low of 79 months. Bone was the most common site for distant metastasis (70.6 %) followed by liver (54.5 %) and lung (31.4 %), respectively. Visceral metastasis was found in 76.8 % of the patients. Patients with ER-/HER2- tumours developed visceral metastases in 81 % and bone metastases in 55.2 %; those with HER2+ tumours developed visceral metastases in 77.4 % and bone metastases in 69.8 %; those with ER+/HER2-/Ki67high developed visceral metastases in 75.7 % and bone metastases in 87.8 % and those with ER+/HER2-/Ki67low developed visceral metastases in 76.9 % and bone metastases in 73.1 %. In metastatic breast cancer patients, tumour subtypes are associated with survival and pattern of distant metastases. These associations are of help in choices for surveillance and therapy in individual patients.

In this study, our aim was to identify molecular aberrations predictive for response to everolimus, an mTOR inhibitor, regardless of tumor type.

Michiels et al. (Lancet 2005; 365: 488-92) employed a resampling strategy to show that the genes identified as predictors of prognosis from resamplings of a single gene expression dataset are highly variable. The genes most frequently identified in the separate resamplings were put forward as a 'gold standard'. On a higher level, breast cancer datasets collected by different institutions can be considered as resamplings from the underlying breast cancer population. The limited overlap between published prognostic signatures confirms the trend of signature instability identified by the resampling strategy. Six breast cancer datasets, totaling 947 samples, all measured on the Affymetrix platform, are currently available. This provides a unique opportunity to employ a substantial dataset to investigate the effects of pooling datasets on classifier accuracy, signature stability and enrichment of functional categories.

The presence of tumor-infiltrating lymphocytes (TILs) is correlated with good prognosis and outcome after (immuno)therapy in triple-negative and HER2-positive breast cancer. However, the role of TILs in luminal breast cancer is less clear. Emerging evidence has now demonstrated that genetic aberrations in malignant cells influence the immune landscape of tumors. Phosphatidylinositol 3-kinase (PI3K) is the most common altered pathway in ER-positive breast cancer. It is unknown whether changes in the PI3K pathway result in a different composition of the breast tumor microenvironment. Here we present the retrospective analysis of a prospective randomized trial in ER-positive breast cancer on the prognostic and predictive value of specific tumor-associated lymphocytes in the context of PI3K alterations.