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Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.

Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.

In recent years, biotechnological breakthroughs have led to identification of complex and unique biologic features associated with carcinogenesis. Tumor and cell-free DNA profiling, immune markers, and proteomic and RNA analyses are used to identify these characteristics for optimization of anticancer therapy in individual patients. Consequently, clinical trials have evolved, shifting from tumor type-centered to gene-directed, histology-agnostic, with innovative adaptive design tailored to biomarker profiling with the goal to improve treatment outcomes. A plethora of precision medicine trials have been conducted. The majority of these trials demonstrated that matched therapy is associated with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To improve the implementation of precision medicine, this approach should be used early in the course of the disease, and patients should have complete tumor profiling and access to effective matched therapy. To overcome the complexity of tumor biology, clinical trials with combinations of gene-targeted therapy with immune-targeted approaches (e.g., checkpoint blockade, personalized vaccines and/or chimeric antigen receptor T-cells), hormonal therapy, chemotherapy and/or novel agents should be considered. These studies should target dynamic changes in tumor biologic abnormalities, eliminating minimal residual disease, and eradicating significant subclones that confer resistance to treatment. Mining and expansion of real-world data, facilitated by the use of advanced computer data processing capabilities, may contribute to validation of information to predict new applications for medicines. In this review, we summarize the clinical trials and discuss challenges and opportunities to accelerate the implementation of precision oncology.

Background/Aim: The application of next generation sequencing (NGS) technology in the genetic investigation of hereditary cancer is important for clinical surveillance, therapeutic approach, and reducing the risk of developing new malignancies. The aim of the study was to explore genetic predisposition in individuals referred for hereditary cancer. Materials and Methods: A total of 8,261 individuals were referred for multigene genetic testing, during the period 2020-2023, in the laboratory, and underwent multigene genetic testing using NGS. Among the examined individuals, 56.17% were diagnosed with breast cancer, 6.77% with ovarian cancer, 2.88% with colorectal cancer, 1.91% with prostate cancer, 6.43% were healthy with a significant family history of cancer, while 3.06% had a different type of cancer and 0.21% had not provided any information. Additionally, in 85 women with breast cancer we performed whole exome sequencing analysis. Results: 20% of the examined individuals carried a pathogenic variant. Specifically, 54.8% of the patients had a pathogenic variant in a clinically significant gene (BRCA1, BRCA2, PALB2, RAD51C, PMS2, CDKN2A, MLH1, MSH2, TP53, MSH6, APC, RAD51D, PTEN, RET, CDH1, MEN1, and VHL). Among the different types of pathogenic variants detected, a significant percentage (6.52%) represented copy number variation (CNV). With WES analysis, the following findings were detected: CTC1: c.880C>T, p.(Gln294*); MLH3: c.405del, p.(Asp136Metfs*2), PPM1D: c.1426_1430del, p.(Glu476Leufs*3), and SDHB: c.395A>G, p.(His132Arg). Conclusion: Comprehensive multigene genetic testing is necessary for appropriate clinical management of pathogenic variants’ carriers. Additionally, the information obtained is important for determining the risk of malignancy development in family members of the examined individuals. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the most prominent tumor type among women, accounting for 32% of newly diagnosed cancer cases. BC risk factors include inherited germline pathogenic gene variants and family history of disease. However, the etiology of the disease remains occult in most cases. Therefore, in the absence of high-risk factors, a polygenic basis has been suggested to contribute to susceptibility. This information is utilized to calculate the Polygenic Risk Score (PRS) which is indicative of BC risk. This study aimed to evaluate retrospectively the clinical usefulness of PRS integration in BC risk calculation, utilizing a group of patients who have already been diagnosed with BC. The study comprised 105 breast cancer patients with hereditary genetic analysis results obtained by NGS. The selection included all testing results: high-risk gene-positive, intermediate/low-risk gene-positive, and negative. PRS results were obtained from an external laboratory (Allelica). PRS-based BC risk was computed both with and without considering additional risk factors, including gene status and family history. A significantly different PRS percentile distribution consistent with higher BC risk was observed in our cohort compared to the general population. Higher PRS-based BC risks were detected in younger patients and in those with FH of cancers. Among patients with a pathogenic germline variant detected, reduced PRS values were observed, while the BC risk was mainly determined by a monogenic etiology. Upon comprehensive analysis encompassing FH, gene status, and PRS, it was determined that 41.90% (44/105) of the patients demonstrated an elevated susceptibility for BC. Moreover, 63.63% of the patients with FH of BC and without an inherited pathogenic genetic variant detected showed increased BC risk by incorporating the PRS result. Our results indicate a major utility of PRS calculation in women with FH in the absence of a monogenic etiology detected by NGS. By combining high-risk strategies, such as inherited disease analysis, with low-risk screening strategies, such as FH and PRS, breast cancer risk stratification can be improved. This would facilitate the development of more effective preventive measures and optimize the allocation of healthcare resources. [ABSTRACT FROM AUTHOR]

Simple Summary: Identification of germline pathogenic variants in breast cancer patients holds significant importance for accurate risk assessment and therapeutic interventions. However, research focusing on very young breast cancer patients remains limited. Our objective was to describe the prevalence, gene, and variant spectra alongside clinicopathological characteristics and outcomes of women diagnosed with breast cancer ≤30 years. Our observations revealed that one in three patients carried predisposing variants distributed in eight established breast cancer genes. Predominantly, causative variants implicated loss-of-function of BRCA1, TP53, and BRCA2, with TP53 emerging as the second most frequently mutated gene within this cohort. While carrier status did not impact event-free survival, carriers who underwent neoadjuvant chemotherapy exhibited improved prognostic outcomes. Our data underscore the substantial proportion of patients with hereditary predisposition, advocate for the inclusion of TP53 genetic testing, and suggest possible benefits of neoadjuvant chemotherapy in this very young group of breast cancer patients. Early-onset breast cancer constitutes a major criterion for genetic testing referral. Nevertheless, studies focusing on breast cancer patients (≤30 years) are limited. We investigated the contribution and spectrum of known breast-cancer-associated genes in 267 Greek women with breast cancer ≤30 years while monitoring their clinicopathological characteristics and outcomes. In this cohort, a significant proportion (39.7%) carried germline pathogenic variants (PVs) distributed in 8 genes. The majority, namely 36.7%, involved BRCA1, TP53, and BRCA2. PVs in BRCA1 were the most prevalent (28.1%), followed by TP53 (4.5%) and BRCA2 (4.1%) PVs. The contribution of PVs in CHEK2, ATM, PALB2, PTEN, and RAD51C was limited to 3%. In the patient group ≤26 years, TP53 PVs were significantly higher compared to the group 26–30 years (p = 0.0023). A total of 74.8% of TP53 carriers did not report a family history of cancer. Carriers of PVs receiving neoadjuvant chemotherapy showed an improved event-free survival (p < 0.0001) compared to non-carriers. Overall, many women with early-onset breast cancer carry clinically actionable variants, mainly in the BRCA1/2 and TP53 genes. The inclusion of timely testing of TP53 in these patients provides essential information for appropriate clinical management. This is important for countries where reimbursement involves the cost of genetic analysis of BRCA1/2 only. [ABSTRACT FROM AUTHOR]

PURPOSE: The pan-cancer presence of microsatellite instability (MSI)–positive tumors demonstrates its clinical utility as an agnostic biomarker for identifying immunotherapy-eligible patients. Additionally, MSI is a hallmark of Lynch syndrome (LS), the most prevalent cancer susceptibility syndrome among patients with colorectal and endometrial cancer. Therefore, MSI-high results should inform germline genetic testing for cancer-predisposing genes. However, in clinical practice, such analysis is frequently disregarded. METHODS: A next-generation sequencing (NGS)–based technique was used for MSI analysis in 4,553 patients with various tumor types. Upon request, somatic BRAF gene analysis was conducted. In addition, hereditary testing of cancer-associated genes was performed in MSI-high cases using a capture-based NGS protocol. MLH1 promoter methylation analysis was conducted retrospectively in patients with colorectal and endometrial cancer to further investigate the origin of MSI at the tumor level. RESULTS: The MSI positivity rate for the entire cohort was 5.27%. Endometrial, gastric, colorectal, urinary tract, and prostate cancers showed the highest proportion of MSI-high cases (15.69%, 8.54%, 7.40%, 4.55%, and 3.19%, respectively). A minority of 45 patients (22.73%) among the MSI-high cases underwent germline testing to determine whether the mismatch repair pathway deficiency was inherited. 24.44% of those who performed the genetic test carried a pathogenic variant in an LS-associated gene. Three MSI-high individuals had non-LS gene alterations, including BRCA1 , BRCA2 , and CDKN2A pathogenic variants, indicating the presence of non–LS-associated gene alterations among MSI-high patients. CONCLUSION: Although MSI analysis is routinely performed in clinical practice, as many as 77% of MSI-high patients do not undergo LS genetic testing, despite international guidelines strongly recommending it. BRAF and MLH1 methylation analysis could shed light on the somatic origin of MSI in 42.50% of the MSI-high patients; however, MLH1 analysis is barely ever requested in clinical practice. [ABSTRACT FROM AUTHOR]