Background: Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments. Methods: We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected. Results: Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84–0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality. Conclusion: Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC.

A thorough study of Clear Cell Renal Cell Carcinoma (ccRCC) shows that combining tyrosine kinase inhibitors (TKI) with immune checkpoint inhibitors (ICI) shows promising results in addressing the tumor-promoting influences of abnormal immunological and molecular biomarkers in metastatic Clear Cell Renal Cell Carcinoma (ccRCC). These abnormal biomarkers enhance drug resistance, support tumor growth, and trigger cancer-related genes. Ongoing clinical trials are testing new treatment options that appear more effective than earlier ones. However, more research is needed to confirm their long-term safety use and potential side effects. This study highlights vital molecular and immunological biomarkers associated with drug resistance in Clear Cell Renal Cell Carcinoma (ccRCC). Furthermore, this study identifies a number of promising drug candidates and biomarkers that serve as significant contributors to the enhancement of the overall survival of ccRCC patients. Consequently, this article offers pertinent insights on both recently completed and ongoing clinical trials, recommending further toxicity study for the prolonged use of this treatment strategy for patients with metastatic ccRCC, while equipping researchers with invaluable information for the progression of current treatment strategies.

Regardless of the presence or absence of specific diagnostic mutations, many cancer patients fail to respond to EGFR-targeted therapeutics, and a personalized approach is needed to identify putative (non)responders. We found previously that human peripheral blood and EGF can modulate the activities of EGFR-specific drugs on inhibiting clonogenity in model EGFR-positive A431 squamous carcinoma cells. Here, we report that human serum can dramatically abolish the cell growth rate inhibition by EGFR-specific drugs cetuximab and erlotinib. We show that this phenomenon is linked with derepression of drug-induced G1S cell cycle transition arrest. Furthermore, A431 cell growth inhibition by cetuximab, erlotinib, and EGF correlates with a decreased activity of ERK1/2 proteins. In turn, the EGF- and human serum-mediated rescue of drug-treated A431 cells restores ERK1/2 activity in functional tests. RNA sequencing revealed 1271 and 1566 differentially expressed genes (DEGs) in the presence of cetuximab and erlotinib, respectively. Erlotinib- and cetuximab-specific DEGs significantly overlapped. Interestingly, the expression of 100% and 75% of these DEGs restores to the no-drug level when EGF or a mixed human serum sample, respectively, is added along with cetuximab. In the case of erlotinib, EGF and human serum restore the expression of 39% and 83% of DEGs, respectively. We further assessed differential molecular pathway activation levels and propose that EGF/human serum-mediated A431 resistance to EGFR drugs can be largely explained by reactivation of the MAPK signaling cascade.

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants.

Background: According to epidemiological studies, endometrial carcinoma is one of the most frequently diagnosed malignancies of the female reproductive system, with an increasing incidence. Currently, the risk stratification of this neoplasm takes into account the stage, degree of tumor differentiation, histological type and depth of myometrial invasion. Since the publication of the last International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer in 2009, numerous reports have appeared on the molecular characteristics of different types of endometrial carcinoma. Taking this into account, the FIGO Committee determined in 2023 that changes and updates to the staging system are justified to reflect new information about this tumor. Due to the high prevalence of the disease and mortality from endometrial cancer, an in-depth study of the molecular genetic characteristics of tumor cells is relevant; the results of such studies can be used to improve the efficiency of diagnosis, assess the risk of metastasis and prognosis of the disease. Lymph node assessment is crucial for the choice of treatment strategy for endometrial cancer, since metastatic lymph node involvement is one of the main factors affecting prognosis. At the same time, the criteria for the appropriateness of lymphadenectomy in low-differentiated malignant tumors are not clearly defined. Various molecular methods have been proposed to assess the status of lymph nodes; candidate genes are being studied as potential diagnostic biomarkers, as well as microRNA. The aim of the study was to analyze the literature data on numerous studies of molecular risk factors for progression in endometrioid carcinoma, as well as to preserve the most important marker changes in relation to the prognostic development of this disease. Methods: A literature review was conducted using data from the electronic databases PubMed, Google Scholar, and Wiley Cochrane Library for the period from 2018 to 2023 using the specific keywords. Results: The current scientific genetic studies on metastasis and prognostic factors in uterine cancer were analyzed, and a systematization of the reviewed data from the modern literature was done. Conclusions: To select the most effective treatment - intraoperative, adjuvant or combination therapy, minimize postoperative risks of lymphadenectomy and clearly predict the results - further study of the molecular genetic features of endometrial cancer is necessary.

Lung cancer accounts for the majority of cancer cases. In recent years, checkpoint inhibitor immunotherapy (ICI) has emerged as a new treatment. A better understanding of the tumor microenvironment, or TMJ, or the immune system surrounding the tumor is needed. Cytokines are small proteins that carry messages between cells and are known to play an important role in the body's response to inflammation and infection. Cytokines are important for immunity in lung cancer. It promotes tumor growth (oncogenic cytokines) or inhibits tumor growth (anti-tumor cytokines) by controlling signaling pathways for growth, proliferation, metastasis, and apoptosis. The immune system relies heavily on cytokines. They can also be produced in the laboratory for therapeutic use. Cytokine therapy helps the immune system stop the growth or kill cancer cells. Interleukins and interferons are two types of cytokines used to treat cancer. This article begins by addressing the role of the tumor microenvironment (TMJ) and its components in lung cancer. This review also highlights the functions of various cytokines such as IL, TGF and TNF.