Breast and ovarian cancers are some of the most common tumors in females, and the genetic predisposition is emerging as one of the key risk factors in the development of these two malignancies. BRCA1 and BRCA2 are the best-known genes associated with hereditary breast and ovarian cancer. However, recent advances in molecular techniques, Next-Generation Sequencing in particular, have led to the identification of many new genes involved in the predisposition to breast and/or ovarian cancer, with different penetrance estimates. TP53, PTEN, STK11, and CDH1 have been identified as high penetrance genes for the risk of breast/ovarian cancers. Besides them, PALB2, BRIP1, ATM, CHEK2, BARD1, NBN, NF1, RAD51C, RAD51D and mismatch repair genes have been recognized as moderate and low penetrance genes, along with other genes encoding proteins involved in the same pathways, possibly associated with breast/ovarian cancer risk. In this review, we summarize the past and more recent findings in the field of cancer predisposition genes, with insights into the role of the encoded proteins and the associated genetic disorders. Furthermore, we discuss the possible clinical utility of genetic testing in terms of prevention protocols and therapeutic approaches.

Circulating tumor cells (CTCs) are a rare population of cells representing a key player in the metastatic cascade. They are recognized as a validated tool for the identification of patients with a higher risk of relapse, including those diagnosed with breast cancer (BC). However, CTCs are characterized by high levels of heterogeneity that also involve copy number alterations (CNAs), structural variations associated with gene dosage changes. In this study, single CTCs were isolated from the peripheral blood of 11 early-stage BC patients at different time points. A label-free enrichment of CTCs was performed using OncoQuick, and single CTCs were isolated using DEPArray. Libraries were prepared from single CTCs and DNA extracted from matched tumor tissues for a whole-genome low-coverage next-generation sequencing (NGS) analysis using the Ion Torrent S5 System. The analysis of the CNA burden highlighted that CTCs had different degrees of aberration based on the time point and subtype. CTCs were found even six months after surgery and shared CNAs with matched tumor tissue. Tumor-associated CNAs that were recurrent in CTCs were patient-specific, and some alterations involved regions associated with BC and survival (i.e., gains at 1q21-23 and 5p15.33). The enrichment analysis emphasized the involvement of aberrations of terms, associated in particular with interferon (IFN) signaling. Collectively, our findings reveal that these aberrations may contribute to understanding the molecular mechanisms involving CTC-related processes and their survival ability in occult niches, supporting the goal of exploiting their application in patients’ surveillance and follow-up.

Circulating tumor DNA predicts prognosis of mCRC patients receiving first-line bevacizumab based-chemotherapy

There are no accepted universal biomarkers capable to accurately predict response to immuno-checkpoint inhibitors (ICI). Although recent literature has been flooded with studies on ICI predictive biomarkers, available data show that currently approved companion diagnostics either leave out many possible responders, as in the case of PD-L1 testing for first-line metastatic lung cancer, or apply to a small subset of patients, such as the recently approved treatment for microsatellite instability-high or mismatch repair deficiency tumors. In this study, we conducted a survey of the available data on ICI trials with matched genomic or transcriptomic datasets in order to cross-validate the proposed biomarkers, to assess whether their prediction power was confirmed and, mainly, to investigate if their combination was able to generate a better predictive tool. We extracted clinical information and sequencing data details from publicly available datasets, along with a list of possible biomarkers obtained from the recent literature. After an operation of data harmonization, we validated the performance of all the biomarkers taken individually. Furthermore, we tested two strategies to combine the best performing biomarkers in order to improve their predictive value. When considered individually, some of the biomarkers, such as the ImmunoPhenoScore, and the IFN-γ signature, did not confirm their originally proposed predictive power. The best absolute scoring biomarkers are TIDE, one of the ICB resistance signatures and CTLA4 with a mean AUC > 0.66. Among the combinations tested, generalized linear models showed the best performance with an AUC of 0.78. We confirmed that the available biomarkers, taken individually, fail to provide a satisfactory predictive value. Unfortunately, also combination of some of them only provides marginal improvements. Hence, in order to generate a more robust way to predict ICI efficacy it is necessary to analyze and combine additional biomarkers and interrogate a wider set of clinical data.

Circulating tumor cells’ (CTCs) heterogeneity contributes to counteract their introduction in clinical practice. Through single-cell sequencing we aim at exploring CTC heterogeneity in metastatic breast cancer (MBC) patients. Single CTCs were isolated using DEPArray NxT. After whole genome amplification, libraries were prepared for copy number aberration (CNA) and single nucleotide variant (SNV) analysis and sequenced using Ion GeneStudio S5 and Illumina MiSeq, respectively. CTCs demonstrate distinctive mutational signatures but retain molecular traces of their common origin. CNA profiling identifies frequent aberrations involving critical genes in pathogenesis: gains of 1q (CCND1) and 11q (WNT3A), loss of 22q (CHEK2). The longitudinal single-CTC analysis allows tracking of clonal selection and the emergence of resistance-associated aberrations, such as gain of a region in 12q (CDK4). A group composed of CTCs from different patients sharing common traits emerges. Further analyses identify losses of 15q and enrichment of terms associated with pseudopodium formation as frequent and exclusive events. CTCs from MBC patients are heterogeneous, especially concerning their mutational status. The single-cell analysis allows the identification of aberrations associated with resistance, and is a candidate tool to better address treatment strategy. The translational significance of the group populated by similar CTCs should be elucidated.