Predictive Biomarkers Research Articles

Differential proteomics of circulating extracellular vesicles of placental origin isolated from women with early-onset preeclampsia reveal aberrant innate immune and hemostasis processes.

Early-onset preeclampsia (EOPE) is a severe gestational hypertensive disorder with significant feto-maternal morbidity and mortality due to uteroplacental insufficiency. Circulating extracellular vesicles of placental origin (EV-P) are known to be involved in the pathophysiology of EOPE and might serve as an ideal reservoir for its specific biomarkers. Therefore, we aimed to characterize and perform comparative proteomics of circulating EV-P from healthy pregnant and EOPE women before delivery. The EV-P from both groups were isolated using immunoaffinity and were characterized using transmission electron microscopy, dynamic light scattering, nanoparticle tracking analysis, and immunoblotting. Following IgG albumin depletion, the pooled proteins that were isolated from EV-P of both groups were subjected to quantitative TMT proteomics. Circulating term EV-P isolated from both groups revealed ∼150nm spherical vesicles containing CD9 and CD63 along with placental PLAP and HLA-G proteins. Additionally, the concentration of EOPE-derived EV-P was significantly increased. A total of 208 proteins were identified, with 26 among them being differentially abundant in EV-P of EOPE women. This study linked the pathophysiology of EOPE to 19 known and seven novel proteins associated with innate immune responses such as complement and TLR signaling along with hemostasis and oxygen homeostasis. The theory suggesting circulating EVs of placental origin could mimic molecular information from the parent organ-"the placenta"-is strengthened by this study. The findings pave the way for possible discovery of novel prognostic and predictive biomarkers as well as provide insight into the mechanisms driving the pathogenesis of EOPE.

Characterization of the dehydrogenase-reductase DHRS2 and its involvement in histone deacetylase inhibition in urological malignancies.

Being implicated during tumor migration, invasion, clonogenicity, and proliferation, the nicotinamide adenine dinucleotide (NAD)/-phosphate (NADP)-dependent dehydrogenase/reductase member 2 (DHRS2) has been considered to be induced upon inhibition of histone deacetylases (HDACi). In this study, we evaluated the current knowledge on the underlying mechanisms of the (epi)genetic regulation of DHRS2, as well as its function during tumor progression. DHRS2 expression was evaluated on mRNA- and protein-level upon treatment with HDACi by means of qRT-PCR and western blot analyses, respectively. Re-analysis of RNA-sequencing data gained insight into expression of specific DHRS2 isoforms, while re-analysis of ATAC-sequencing data shed light on the chromatin accessibility at the DHRS2 locus. Further examination of the energy and lipid metabolism of HDACi-treated urologic tumor cells was performed using liquid chromatography-mass spectrometry. Enhanced DHRS2 expression levels upon HDACi treatment were directly linked to an enhanced chromatin accessibility at the DHRS2 locus. Particularly the DHRS2 ENST00000250383.11 protein-coding isoform was increased upon HDACi treatment. Application of the HDACi quisinostat only mildly influenced the energy metabolism of urologic tumor cells, though, the analysis of the lipid metabolism showed diminished sphingosine levels, as well as decreased S1P levels. Also the ratios of S1P/sphingosine and S1P/ceramides were reduced in all four quisinostat-treated urologic tumor cells. With the emphasis on urologic malignancies (testicular germ cell tumors, urothelial, prostate, and renal cell carcinoma), this study concluded that elevated DHRS2 levels are indicative of a successful HDACi treatment and, thereby offering a novel putative predictive biomarker.

Absence of ATM leads to altered NK cell function in mice

Ataxia-telangiectasia (A-T) is a rare disorder caused by genetic defects of A-T mutated (ATM) kinase, a key regulator of stress response, and characterized by neurodegeneration, immunodeficiency, and high incidence of cancer. Here we investigated NK cells in a mouse model of A-T (Atm−/−) showing that they are strongly impaired at killing tumor cells due to a block of early signaling events. On the other hand, in Atm−/− littermates with thymic lymphoma NK cell cytotoxicity is enhanced as compared with ATM-proficient mice, possibly via tumor-produced TNF-α. Results also suggest that expansion of exhausted NKG2D+ NK cells in Atm−/− mice is driven by low-level expression of stress-inducible NKG2D ligands, whereas development of thymoma expressing the high-affinity MULT1 ligand is associated with NKG2D down-regulation on NK cells.These results expand our understanding of immunodeficiency in A-T and encourage exploring NK cell biology in A-T patients in the attempt to identify cancer predictive biomarkers and novel therapeutic targets.

Immunotherapy in Colorectal Cancer - Finding the Achilles' Heel.

AbstractColorectal cancer treatment has evolved considerably in the last decade with the development of immunotherapies. Immune checkpoint inhibitor therapies have brisk and durable responses in patients with advanced microsatellite instability-high colorectal cancer, both surgically resectable and unresectable; however, patients with microsatellite stable colorectal cancer in general do not respond to the same therapy. Emerging evidence shows that immune checkpoint inhibitors may elicit responses in subsets of patients with microsatellite stable colorectal cancer, especially when combined with other anticancer agents that can modulate the tumor microenvironment. Therefore, rationally designed therapeutic combinations involving immune checkpoint inhibitors, as well as the development of predictive biomarkers for optimal patient selection, have emerged as two key areas of active research. In addition, other immunotherapeutic agents such as cell-based therapies and bispecific T-cell engagers are beginning to be studied in preclinical and early-phase settings. Although by no means a universal treatment strategy, immunotherapy can elicit responses in microsatellite stable colorectal cancer and further research is needed to extend their benefit to patients with microsatellite stable colorectal cancer. Here, we review the current state of immunotherapeutic regimens for microsatellite stable colorectal cancer.

Quantification of multiple steroid hormones in serum and human breast cancer tissue by liquid chromatography-tandem mass spectrometry analysis

IntroductionSystemic and local steroid hormone levels may function as novel prognostic and predictive biomarkers in breast cancer patients. We aimed at developing a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous measurement of multiple, biologically pivotal steroid hormones in human serum and breast cancer tissue.MethodsThe quantitative method consisted of liquid-liquid extraction, Sephadex LH-20 chromatography for tissue extracts, and analysis of steroid hormones by liquid-chromatography-tandem mass spectrometry. We analyzed serum and tissue steroid hormone levels in 16 and 40 breast cancer patients, respectively, and assessed their correlations with clinical parameters.ResultsThe method included quantification of nine steroid hormones in serum [including cortisol, cortisone, corticosterone, estrone (E1), 17β-estradiol (E2), 17α-hydroxyprogesterone, androstenedione (A4), testosterone and progesterone) and six (including cortisone, corticosterone, E1, E2, A4, and testosterone) in cancer tissue. The lower limits of quantification were between 0.003–10 ng/ml for serum (250 µl) and 0.038–125 pg/mg for tissue (20 mg), respectively. Accuracy was between 98%-126%, intra-assay coefficient of variations (CV) was below 15%, and inter-assay CV were below 11%. The analytical recoveries for tissue were between 76%-110%. Tissue levels of E1 were positively correlated with tissue E2 levels (p<0.001), and with serum levels of E1, E2 and A4 (p<0.01). Tissue E2 levels were positively associated with serum E1 levels (p=0.02), but not with serum E2 levels (p=0.12). The levels of tissue E2 and ratios of E1 to A4 levels (an index for aromatase activity) were significantly higher in patients with larger tumors (p=0.03 and p=0.02, respectively).ConclusionsThe method was convenient and suitable for a specific and accurate profiling of clinically important steroid hormones in serum. However, the sensitivity of the profile method in steroid analysis in tissue samples is limited, but it can be used for the analysis of steroids in breast cancer tissues if the size of the sample or its steroid content is sufficient.

Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer

Gastric cancer (GC) is one of the most common cancers worldwide. Most patients are diagnosed at the progressive stage of the disease, and current anticancer drug advancements are still lacking. Therefore, it is crucial to find relevant biomarkers with the accurate prediction of prognoses and good predictive accuracy to select appropriate patients with GC. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have enabled the approach of GC biology at multiple levels of omics interaction networks. Systemic biological analyses, such as computational inference of “big data” and advanced bioinformatic approaches, are emerging to identify the key molecular biomarkers of GC, which would benefit targeted therapies. This review summarizes the current status of how bioinformatics analysis contributes to biomarker discovery for prognosis and prediction of therapeutic efficacy in GC based on a search of the medical literature. We highlight emerging individual multi-omics datasets, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for validating putative markers. Finally, we discuss the current challenges and future perspectives to integrate multi-omics analysis for improving biomarker implementation. The practical integration of bioinformatics analysis and multi-omics datasets under complementary computational analysis is having a great impact on the search for predictive and prognostic biomarkers and may lead to an important revolution in treatment.

Editorial: Novel and potential biomarkers for prediction of outcome in patients with chronic and acute coronary heart disease, volume II

Editorial: Novel and potential biomarkers for prediction of outcome in patients with chronic and acute coronary heart disease, volume II

Advancements and challenges in triple-negative breast cancer: a comprehensive review of therapeutic and diagnostic strategies

Triple-negative breast cancer (TNBC) poses significant challenges in oncology due to its aggressive nature, limited treatment options, and poorer prognosis compared to other breast cancer subtypes. This comprehensive review examines the therapeutic and diagnostic landscape of TNBC, highlighting current strategies, emerging therapies, and future directions. Targeted therapies, including PARP inhibitors, immune checkpoint inhibitors, and EGFR inhibitors, hold promise for personalized treatment approaches. Challenges in identifying novel targets, exploring combination therapies, and developing predictive biomarkers must be addressed to optimize targeted therapy in TNBC. Immunotherapy represents a transformative approach in TNBC treatment, yet challenges in biomarker identification, combination strategies, and overcoming resistance persist. Precision medicine approaches offer opportunities for tailored treatment based on tumor biology, but integration of multi-omics data and clinical implementation present challenges requiring innovative solutions. Despite these challenges, ongoing research efforts and collaborative initiatives offer hope for improving outcomes and advancing treatment strategies in TNBC. By addressing the complexities of TNBC biology and developing effective therapeutic approaches, personalized treatments can be realized, ultimately enhancing the lives of TNBC patients. Continued research, clinical trials, and interdisciplinary collaborations are essential for realizing this vision and making meaningful progress in TNBC management.

Trans-activating mutations of the pseudokinase ERBB3.

Genetic changes in the ERBB family of receptor tyrosine kinases serve as oncogenic driver events and predictive biomarkers for ERBB inhibitor drugs. ERBB3 is a pseudokinase member of the family that, although lacking a fully active kinase domain, is well known for its potent signaling activity as a heterodimeric complex with ERBB2. Previous studies have identified few transforming ERBB3 mutations while the great majority of the hundreds of different somatic ERBB3 variants observed in different cancer types remain of unknown significance. Here, we describe an unbiased functional genetics screen of the transforming potential of thousands of ERBB3 mutations in parallel. The screen based on a previously described iSCREAM (in vitro screen of activating mutations) platform, and addressing ERBB3 pseudokinase signaling in a context of ERBB3/ERBB2 heterodimers, identified 18 hit mutations. Validation experiments in Ba/F3, NIH 3T3, and MCF10A cell backgrounds demonstrated the presence of both previously known and unknown transforming ERBB3 missense mutations functioning either as single variants or in cis as a pairwise combination. Drug sensitivity assays with trastuzumab, pertuzumab and neratinib indicated actionability of the transforming ERBB3 variants.

Contrast-enhanced ultrasound features as potential biomarker for prediction of breast cancer recurrence.

Purpose To investigate the associations between contrast-enhanced ultrasound imaging features and disease recurrence among patients with locally advanced breast cancer treated with neoadjuvant chemotherapy. Materials and Methods In the study, pre- and post-neoadjuvant chemotherapy contrast-enhanced ultrasound images of 43 patients with breast cancer were retrospectively analysed. Post-acquisition image processing involved the placement of freehand-drawn regions of interest, followed by the generation of blood flow kinetics representing blood volume and velocity for these regions of interest. Qualitative and quantitative contrast-enhanced ultrasound parameters were compared to predict recurrence, and receiver operating characteristic analysis was used to evaluate predictive ability. Results Among the 43 patients, 10 (23%) exhibited disease recurrence (median [range]: 27 [4-68] months). Post-neoadjuvant chemotherapy peak enhancement, wash-in area under the curve, wash-out area under the curve, and wash-in and wash-out area under the curve (p=0.003, p=0.004, p=0.026, and p=0.014, respectively) differed between the no-recurrence and recurrence groups. The area under the receiver operating characteristic curve (0.88; 95% confidence interval: 0.75-1.00) for post-neoadjuvant chemotherapy peak enhancement was the highest among the contrast-enhanced ultrasound parameters, with a cut-off of 13.33 arbitrary units. Conclusion Higher peak enhancement on post-neoadjuvant chemotherapy contrast-enhanced ultrasound images were associated with recurrence in women with locally advanced breast cancer and is a potential biomarker of tumour recurrence.

Neoadjuvant treatment of pancreatic ductal adenocarcinoma: Whom, when and how

Pancreatic ductal adenocarcinoma (PDAC), which is notorious for its aggressiveness and poor prognosis, remains an area of great unmet medical need, with a 5-year survival rate of 10% - the lowest of all solid tumours. At diagnosis, only 20% of patients have resectable pancreatic cancer (RPC) or borderline RPC (BRPC) disease, while 80% of patients have unresectable tumours that are locally advanced pancreatic cancer (LAPC) or have distant metastases. Nearly 60% of patients who undergo upfront surgery for RPC are unable to receive adequate adjuvant chemotherapy (CHT) because of postoperative complications and early cancer recurrence. An important paradigm shift to achieve better outcomes has been the sequence of therapy, with neoadjuvant CHT preceding surgery. Three surgical stages have emerged for the preoperative assessment of nonmetastatic pancreatic cancers: RPC, BRPC, and LAPC. The main goal of neoadjuvant treatment (NAT) is to improve postoperative outcomes through enhanced selection of candidates for curative-intent surgery by identifying patients with aggressive or metastatic disease during initial CHT, reducing tumour volume before surgery to improve the rate of margin-negative resection (R0 resection, a microscopic margin-negative resection), reducing the rate of positive lymph node occurrence at surgery, providing early treatment of occult micrometastatic disease, and assessing tumour chemosensitivity and tolerance to treatment as potential surgical criteria. In this editorial, we summarize evidence concerning NAT of PDAC, providing insights into future practice and study design. Future research is needed to establish predictive biomarkers, measures of therapeutic response, and multidisciplinary strategies to improve patient-centered outcomes.

Integrative analysis indicates the potential values of ANKRD53 in stomach adenocarcinoma.

Ankyrin repeat domain 53 (ANKRD53) plays an important role in maintaining chromosome integrity and stability, and chromosome instability is associated with cancer. Through integrative analysis, this study investigates the potential value of ANKRD53 in stomach adenocarcinoma (STAD). RNA-seq and scRNA-seq data were used for integrative analysis based on online databases. Expression of ANKRD53 was confirmed by RT-PCR after bioinformatic analysis. Kaplan-Meier and Cox regression analyses were performed to evaluate the prognostic value of ANKRD53 in STAD. Gene set enrichment analysis (GSEA) was performed to evaluate ANKRD53-related signaling pathways. In addition, the interaction of ANKRD53 with immunity was also investigated. RT-PCR in STAD cell lines confirmed that ANKRD53 was downregulated in STAD samples compared to normal samples in the online databases. As an independent predictive biomarker, ANKRD53 was combined with other clinicopathological parameters to create a prognostic nomogram. Using GSEA, ANKRD53 was found to be involved in five pathways, including the TGF-β signaling pathway. Further investigation revealed that ANKRD53 was associated with immune checkpoint molecules, immunological pathways, and immunotherapy, in addition to MSI, TMB and neoantigens. In addition, scRNA-seq data revealed that ANKRD53 is mainly expressed in CD8+ T and dendritic cells. ANKRD53 is an important biomarker for STAD that deserves further attention.

Integrated analysis of tumor-associated macrophages and M2 macrophages in CRC: unraveling molecular heterogeneity and developing a novel risk signature.

Emerging investigations have increasingly highlighted the critical role of tumor-associated macrophages (TAMs) and M2 macrophages in cancer development, progression, and metastasis, marking them as potential targets in various cancer types. The main objective of this research is to discover new biomarkers associated with TAM-M2 macrophages in colorectal cancer (CRC) and to dissect the molecular heterogeneity of CRC by combining single-cell RNA sequencing and bulk RNA-seq data. By utilizing weighted gene co-expression network analysis (WGCNA), we acquired TAM-M2-associated genes by intersecting TAM marker genes obtained from scRNA-seq data with module genes of M2 macrophages derived from bulk RNA-seq data. We employed least absolute shrinkage and selection operator (LASSO) Cox analysis to select predictive biomarkers from these TAM-M2-related genes. Quantitative polymerase chain reaction (qPCR) was employed to validate the mRNA expression levels of the genes identified in the screening. This led to the development of the TAM-M2-related signature (TAMM2RS). We also conducted functional and immune landscape analyses of different risk groups. The combination of scRNA-seq and bulk RNA-seq analyses yielded 377 TAM-M2-related genes. DAPK1, NAGK, and TRAF1 emerged as key prognostic genes in CRC, which were identified through LASSO Cox analysis. Utilizing these genes, we constructed and validated the TAMM2RS, demonstrating its effectiveness in predicting survival in CRC patients. Our research offers a thorough investigation into the molecular mechanisms associated with TAM-M2 macrophages in CRC and unveils potential therapeutic targets, offering new insights for treatment strategies in colorectal cancer.

Gene Abnormalities and Modulated Gene Expression Associated with Radionuclide Treatment: Towards Predictive Biomarkers of Response

Gene Abnormalities and Modulated Gene Expression Associated with Radionuclide Treatment: Towards Predictive Biomarkers of Response

Progress of circulating tumor DNA methylation for gastric cancer screening and management

Circulating tumor DNA (ctDNA) is cell-free DNA released by tumors or circulating tumor cells, containing abundant tumor-specific information that can serve as biomarkers for cancer early screening, monitoring, prognosis, and prediction of treatment response. This is particularly attractive in the field of gastric cancer, where high-quality screening, monitoring, and prediction methods are currently lacking. Gastric cancer exhibits significant tumor heterogeneity, with large differences in genetic and epigenetic characteristics among different subgroups. Methylated ctDNA has high sensitivity and specificity, which can help clarify tumor genotyping and facilitate the formulation of precise diagnostic and therapeutic strategies. Furthermore, numerous studies have confirmed the unique advantages of methylated DNA in predicting treatment response, adjuvant therapy, and drug resistance assessment, which may be used in the future to enhance the efficacy of chemotherapy regimens and improve patient chemotherapeutic response, and even treat multidrug resistance. However, there are several challenges associated with methylated ctDNA, such as low sensitivity and specificity at single-target sites, limited association between some gastric cancer subtypes and ctDNA, off-target risks, and the lack of large-scale and high-quality clinical research evidence. This review mainly summarizes current research on the methylation status of ctDNA in gastric cancer and connects these findings to early screening, recurrence monitoring, and potential treatment opportunities for gastric cancer. With advances in technology and the deepening of interdisciplinary research, ctDNA detection will reveal more disease information and become an essential foundation for gastric cancer research and precision medicine treatment.

A new prognostic model based on gamma-delta T cells for predicting the risk and aiding in the treatment of clear cell renal cell carcinoma

BackgroundccRCC is the prevailing form of RCC, accounting for the majority of cases. The formation of cancer and the body's ability to fight against tumors are strongly connected to Gamma delta (γδ) T cells.MethodsWe examined and analyzed the gene expression patterns of 535 individuals diagnosed with ccRCC and 72 individuals serving as controls, all sourced from the TCGA-KIRC dataset, which were subsequently validated through molecular biology experiments.ResultsIn ccRCC, we discovered 304 module genes (DEGRGs) that were ex-pressed differentially and linked to γδ T cells. A risk model for ccRCC was constructed using 13 differentially DEGRGs identified through univariate Cox and LASSO regression analyses, which were found to be associated with prognosis. The risk model exhibited outstanding performance in both the training and validation datasets. The comparison of immune checkpoint inhibitors and the tumor immune microenvironment between the high- and low-risk groups indicates that immunotherapy could lead to positive results for low-risk patients. Moreover, the inhibition of ccRCC cell proliferation, migration, and invasion was observed in cell culture upon knocking down TMSB10, a gene associated with different types of cancers.ConclusionsIn summary, we have created a precise predictive biomarker using a risk model centered on γδ T cells, which can anticipate clinical results and provide direction for the advancement of innovative targeted therapies.

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

BackgroundPrebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders.ResultsUsing short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial.ConclusionsOur results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

Myeloid-derived suppressor cells in peripheral blood as predictive biomarkers in patients with solid tumors undergoing immune checkpoint therapy: systematic review and meta-analysis

BackgroundImmunotherapeutic approaches, including immune checkpoint inhibitor (ICI) therapy, are increasingly recognized for their potential. Despite notable successes, patient responses to these treatments vary significantly. The absence of reliable predictive and prognostic biomarkers hampers the ability to foresee outcomes. This meta-analysis aims to evaluate the predictive significance of circulating myeloid-derived suppressor cells (MDSC) in patients with solid tumors undergoing ICI therapy, focusing on progression-free survival (PFS) and overall survival (OS).MethodsA comprehensive literature search was performed across PubMed and EMBASE from January 2007 to November 2023, utilizing keywords related to MDSC and ICI. We extracted hazard ratios (HRs) and 95% confidence intervals (CIs) directly from the publications or calculated them based on the reported data. A hazard ratio greater than 1 indicated a beneficial effect of low MDSC levels. We assessed heterogeneity and effect size through subgroup analyses.ResultsOur search yielded 4,023 articles, of which 17 studies involving 1,035 patients were included. The analysis revealed that patients with lower levels of circulating MDSC experienced significantly improved OS (HR=2.13 [95% CI 1.51–2.99]) and PFS (HR=1.87 [95% CI 1.29–2.72]) in response to ICI therapy. Notably, heterogeneity across these outcomes was primarily attributed to differences in polymorphonuclear MDSC (PMN-MDSC) subpopulations and varying cutoff methodologies used in the studies. The monocytic MDSC (M-MDSC) subpopulation emerged as a consistent and significant prognostic marker across various subgroup analyses, including ethnicity, tumor type, ICI target, sample size, and cutoff methodology.ConclusionsOur findings suggest that standardized assessment of MDSC, particularly M-MDSC, should be integral to ICI therapy strategies. These cells hold the promise of identifying patients at risk of poor response to ICI therapy, enabling tailored treatment approaches. Further research focusing on the standardization of markers and validation of cutoff methods is crucial for integrating MDSC into clinical practice.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023420095, identifier CRD42023420095.

A synthetic lethal dependency on casein kinase 2 in response to replication-perturbing therapeutics in RB1-deficient cancer cells.

Resistance to therapy commonly develops in patients with high-grade serous ovarian carcinoma (HGSC) and triple-negative breast cancer (TNBC), urging the search for improved therapeutic combinations and their predictive biomarkers. Starting from a CRISPR knockout screen, we identified that loss of RB1 in TNBC or HGSC cells generates a synthetic lethal dependency on casein kinase 2 (CK2) for surviving the treatment with replication-perturbing therapeutics such as carboplatin, gemcitabine, or PARP inhibitors. CK2 inhibition in RB1-deficient cells resulted in the degradation of another RB family cell cycle regulator, p130, which led to S phase accumulation, micronuclei formation, and accelerated PARP inhibition-induced aneuploidy and mitotic cell death. CK2 inhibition was also effective in primary patient-derived cells. It selectively prevented the regrowth of RB1-deficient patient HGSC organoids after treatment with carboplatin or niraparib. As about 25% of HGSCs and 40% of TNBCs have lost RB1 expression, CK2 inhibition is a promising approach to overcome resistance to standard therapeutics in large strata of patients.

Lung microbiome in lung cancer: A new horizon in cancer study.

Lung cancer (LC) is the second most prevalent cancer worldwide and a leading cause of cancer-related deaths. Recent technological advancements have revealed that the lung microbiome, previously thought to be sterile, is host to various microorganisms. The association between the lung microbiome and LC initiation, progression, and metastasis is complex and contradictory. However, disruption in the homeostasis of microbiome compositions correlated with the increased risk of LC. This review summarises current knowledge on the most recent developments and trends in lung cancer-related microbiota or microbial components. This manuscript aims to provide information on this rapidly evolving field while giving context to the general role of the lung microbiome in LC. In addition, this review briefly discussed the causative association of lung microbiome with LC. We will review the mechanisms of how lung microbiota influences carcinogenesis, focusing on microbiota dysbiosis. Moreover, we will also discuss the host-microbiome interaction as host-microbiota plays a crucial role in stimulating and regulating the immune response. Finally, we provide information on the diagnostic role of the microbiome in LC. It aims to offer an overview of the lung microbiome as a predictive and diagnostic biomarker in LC.