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Single cell computational analysis has emerged as a powerful tool in the field of oncology, enabling researchers to decipher the complex cellular heterogeneity that characterizes cancer. By leveraging computational algorithms and bioinformatics approaches, this methodology provides insights into the underlying genetic, epigenetic and transcriptomic variations among individual cancer cells. In this paper, we present a comprehensive overview of single cell computational analysis in oncology, discussing the key computational techniques employed for data processing, analysis, and interpretation. We explore the challenges associated with single cell data, including data quality control, normalization, dimensionality reduction, clustering, and trajectory inference. Furthermore, we highlight the applications of single cell computational analysis, including the identification of novel cell states, the characterization of tumor subtypes, the discovery of biomarkers, and the prediction of therapy response. Finally, we address the future directions and potential advancements in the field, including the development of machine learning and deep learning approaches for single cell analysis. Overall, this paper aims to provide a roadmap for researchers interested in leveraging computational methods to unlock the full potential of single cell analysis in understanding cancer biology with the goal of advancing precision oncology. For this purpose, we also include a notebook that instructs on how to apply the recommended tools in the Preprocessing and Quality Control section. [ABSTRACT FROM AUTHOR]

Esophageal cancer is a common malignant tumor with a high incidence and a serious threat to human health. The treatment of esophageal cancer is a complex process, which requires the comprehensive use of a variety of treatment methods. At present, the treatment of esophageal cancer mainly includes surgery, radiotherapy, chemotherapy and immunotherapy. The research on the treatment of cancer cells based on Goal directed fluid therapy (GDFT) combined with rehabilitation therapy is the focus of the current society. This paper proposed a study on DNA damage repair of cancer cells based on goal directed fluid therapy combined with rehabilitation therapy, aiming to optimize the traditional treatment of esophageal cancer by using goal directed fluid therapy technology. The algorithm proposed in this paper was an electroencephalogram (EEG) signal optimization algorithm based on combined rehabilitation therapy. Through this algorithm, the electroencephalogram signal could be optimized. The algorithm could speed up signal processing, and improve signal reliability and stability by reducing the influence of interference signals and improving the signal to noise ratio. These optimization measures could better help researchers analyze and understand electroencephalogram signals, so as to help better study brain functions and diseases. Through the test and investigation on the treatment of cancer cells based on goal directed fluid therapy combined with rehabilitation therapy, the results showed that the blood transfusion volume of goal directed fluid therapy treatment and conventional treatment was 251.5 mL and 288.3 mL respectively. This showed that after goal directed fluid therapy treatment, the input amount of various medical fluids was relatively reduced, and the use of medical fluids was more economical. In addition, their bleeding volumes were 295.2 mL and 324.4 mL, respectively. Urine volume was 382.3 mL and 418.1 mL respectively. This showed that after goal directed fluid therapy treatment, the patient's blood loss and urine volume were relatively reduced, which has improved the patient's health. This experiment has proved the excellent ability of goal directed fluid therapy combined with rehabilitation therapy in the treatment of esophageal cancer, and this research result has also proved the excellent medical effect of goal directed fluid therapy technology. Similarly, this paper also provided valuable reference information for the treatment of esophageal cancer. [ABSTRACT FROM AUTHOR]

Breast cancer is the malignant tumor with the highest incidence rate at present, and its incidence rate ranks first in the female population. COL11A1 is an important component of collagen XI and is considered to play an important role in a variety of connective tissue diseases. Recent studies have shown that COL11A1 is associated with the occurrence and development of many kinds of malignant tumors. However, its prognostic value in breast cancer and its correlation with immune cell infiltration in tumor tissue are not clear. In this paper, we reveal the prognostic value of COL11A1 in breast cancer and its tumor immune-related function through in-depth bioinformatics analysis. The expression of COL11A1 is abnormally upregulated in breast cancer and is significantly related to the poor prognosis of breast cancer. In the analysis of the clinical characteristics of the patients, we found that the expression level of COLL11A1 was closely related to lymph node metastasis, PAM50 (Prediction Analysis of Microarray 50) expression, clinical stage and so on. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) all suggest that COL11A1 is related to tumor immunity. Further study found that the COL11A1 expression was significantly correlated with the degree of immune infiltration and the expression of a variety of immune cell markers in tumor tissue. More importantly, COL11A1 can affect the prognosis of breast cancer patients by participating in the regulation of tumor immune infiltration. Therefore, we believe that COL11A1 is a very potential target for diagnosis and treatment of breast cancer. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have hitherto identified several germline variants associated with cancer susceptibility, but the molecular functions of these risk modulators remain largely uncharacterized. Recent studies have begun to uncover the regulatory potential of noncoding GWAS SNPs using epigenetic information in corresponding cancer cell types and matched normal tissues. However, this approach does not explore the potential effect of risk germline variants on other important cell types that constitute the microenvironment of tumor or its precursor. This paper presents evidence that the breast-cancer-associated variant rs3903072 may regulate the expression of CTSW in tumor-infiltrating lymphocytes. CTSW is a candidate tumor-suppressor gene, with expression highly specific to immune cells and also positively correlated with breast cancer patient survival. Integrative analyses suggest a putative causative variant in a GWAS-linked enhancer in lymphocytes that loops to the 3' end of CTSW through three-dimensional chromatin interaction. Our work thus poses the possibility that a cancer-associated genetic variant could regulate a gene not only in the cell of cancer origin but also in immune cells in the microenvironment, thereby modulating the immune surveillance by T lymphocytes and natural killer cells and affecting the clearing of early cancer initiating cells. [ABSTRACT FROM AUTHOR]

Integration of distinct biological data types could provide a comprehensive view of biological processes or complex diseases. The combinations of molecules responsible for different phenotypes form multiple embedded (expression) subspaces, thus identifying the intrinsic data structure is challenging by regular integration methods. In this paper, we propose a novel framework of "Multi-view Subspace Clustering Analysis (MSCA)," which could measure the local similarities of samples in the same subspace and obtain the global consensus sample patterns (structures) for multiple data types, thereby comprehensively capturing the underlying heterogeneity of samples. Applied to various synthetic datasets, MSCA performs effectively to recognize the predefined sample patterns, and is robust to data noises. Given a real biological dataset, i.e., Cancer Cell Line Encyclopedia (CCLE) data, MSCA successfully identifies cell clusters of common aberrations across cancer types. A remarkable superiority over the state-of-the-art methods, such as iClusterPlus, SNF, and ANF, has also been demonstrated in our simulation and case studies. [ABSTRACT FROM AUTHOR]

Background: Focused ultrasound (FUS) has become an important non-invasive therapy for prostate tumor ablation via thermal effects in the clinic. The cavitation effect induced by FUS is applied for histotripsy, support drug delivery, and the induction of blood vessel destruction for cancer therapy. Numerous studies report that cavitation-induced sonoporation could provoke multiple anti-proliferative effects on cancer cells. Therefore, cavitation alone or in combination with thermal treatment is of great interest but research in this field is inadequate. Methods: Human prostate cancer cells (LNCap and PC-3) were exposed to 40 s cavitation using a FUS system, followed by water bath hyperthermia (HT). The clonogenic assay, WST-1 assay, and Transwell® invasion assay, respectively, were used to assess cancer cell clonogenic survival, metabolic activity, and invasion potential. Fluorescence microscopy using propidium iodide (PI) as a probe of cell membrane integrity was used to identify sonoporation. The H2A.X assay and Nicoletti test were conducted in the mechanism investigation to detect DNA double-strand breaks (DSBs) and cell cycle arrest. Immunofluorescence microscopy and flow cytometry were performed to determine the distribution and expression of 5α-reductase (SRD5A). Results: Short FUS shots with cavitation (FUS-Cav) in combination with HT resulted in, respectively, a 2.2, 2.3, and 2.8-fold decrease (LNCap) and a 2.0, 1.5, and 1.6-fold decrease (PC-3) in the clonogenic survival, cell invasiveness and metabolic activity of prostate cancer cells when compared to HT alone. FUS-Cav immediately induced sonoporation in 61.7% of LNCap cells, and the combination treatment led to a 1.4 (LNCap) and 1.6-fold (PC-3) increase in the number of DSBs compared to HT alone. Meanwhile, the combination therapy resulted in 26.68% of LNCap and 31.70% of PC-3 with cell cycle arrest in the Sub-G1 phase and 35.37% of PC-3 with cell cycle arrest in the G2/M phase. Additionally, the treatment of FUSCav combined with HT block the androgen receptor (AR) signal pathway by reducing the relative Type I 5α-reductase (SRD5A1) level to 38.28 ± 3.76% in LNCap cells, and decreasing the relative Type III 5α-reductase 3 (SRD5A3) level to 22.87 ± 4.88% in PC-3 cells, in contrast, the relative SRD5A level in untreated groups was set to 100%. Conclusion: FUS-induced cavitation increases the effects of HT by interrupting cancer cell membranes, inducing the DSBs and cell cycle arrest, and blocking the AR signal pathway of the prostate cancer cells, with the potential to be a promising adjuvant therapy in prostate cancer treatment. [ABSTRACT FROM AUTHOR]

Cancer cells within tumor masses are chronically exposed to stress caused by nutrient deprivation, oxygen limitation, and high metabolic demand. They also accumulate hundreds of mutations, potentially generating aberrant proteins that can induce proteotoxic stress. Finally, cancer cells are exposed to various damages during chemotherapy. In a growing tumor, transformed cells eventually adapt to these conditions, eluding the death-inducing outcomes of signaling cascades triggered by chronic stress. One such extreme outcome is ferroptosis, a form of iron-dependent non-apoptotic cell death mediated by lipid peroxidation. Not surprisingly, the tumor suppressor p53 is involved in this process, with evidence suggesting that it acts as a pro-ferroptotic factor and that its ferroptosis-inducing activity may be relevant for tumor suppression. Missense alterations of the TP53 gene are extremely frequent in human cancers and give rise to mutant p53 proteins (mutp53) that lose tumor suppressive function and can acquire powerful oncogenic activities. This suggests that p53 mutation provides a selective advantage during tumor progression, raising interesting questions on the impact of p53 mutant proteins in modulating the ferroptotic process. Here, we explore the role of p53 and its cancer-related mutants in ferroptosis, using a perspective centered on the resistance/sensitivity of cancer cells to exogenous and endogenous stress conditions that can trigger ferroptotic cell death. We speculate that an accurate molecular understanding of this particular axis may improve cancer treatment options. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma (OS) is a kind of solid tumor with high heterogeneity at tumor microenvironment (TME), genome and transcriptome level. In view of the regulatory effect of metabolism on TME, this study was based on four metabolic models to explore the intertumoral heterogeneity of OS at the RNA sequencing (RNA-seq) level and the intratumoral heterogeneity of OS at the bulk RNA-seq and single cell RNAseq (scRNA-seq) level. Methods: The GSVA package was used for single-sample gene set enrichment analysis (ssGSEA) analysis to obtain a glycolysis, pentose phosphate pathway (PPP), fatty acid oxidation (FAO) and glutaminolysis gene sets score. ConsensusClusterPlus was employed to cluster OS samples downloaded from the Target database. The scRNA-seq and bulk RNA-seq data of immune cells from GSE162454 dataset were analyzed to identify the subsets and types of immune cells in OS. Malignant cells and non-malignant cells were distinguished by large-scale chromosomal copy number variation. The correlations of metabolic molecular subtypes and immune cell types with four metabolic patterns, hypoxia and angiogenesis were determined by Pearson correlation analysis. Results: Two metabolism-related molecular subtypes of OS, cluster 1 and cluster 2, were identified. Cluster 2 was associated with poor prognosis of OS, active glycolysis, FAO, glutaminolysis, and bad TME. The identified 28608 immune cells were divided into 15 separate clusters covering 6 types of immune cells. The enrichment scores of 5 kinds of immune cells in cluster-1 and cluster-2 were significantly different. And five kinds of immune cells were significantly correlated with four metabolic modes, hypoxia and angiogenesis. Of the 28,608 immune cells, 7617 were malignant cells. The four metabolic patterns of malignant cells were significantly positively correlated with hypoxia and negatively correlated with angiogenesis. Conclusion: We used RNA-seq to reveal two molecular subtypes of OS with prognosis, metabolic pattern and TME, and determined the composition and metabolic heterogeneity of immune cells in OS tumor by bulk RNA-seq and single-cell RNA-seq. [ABSTRACT FROM AUTHOR]

Background: As a malignant tumor, pancreatic cancer is difficult to detect in its early stage. Pancreatic cancer progresses rapidly and has a short survival time. Most cases have metastasized to distant organs before diagnosis. The mechanism of induction of pancreatic cancer is not fully understood. Methods: In this study, bioinformatics predicted ATP binding cassette subfamily A member 12 (ABCA12) expression in pancreatic tissues and performed survival analysis, risk assessment, and enrichment analysis. The expression of ABCA12 in 30 pairs of clinical samples was detected by immunohistochemistry and we analyzed its correlation with clinical information. Both reverse transcription polymerase chain reaction (RT–PCR) and western blot analysis were used to detect mRNA and protein expression in cell lines. Two different siRNAs and SW1990 cell line were used to construct pancreatic cancer cell models with ABCA12 knockdown. Cell viability was evaluated by cell counting kit-8 (CCK-8) and EdU proliferation assays. Wound healing assays and Transwell assays were used to measure the ability of cell migration and invasion. Flow cytometry was used to investigate the effect of ABCA12 on the proliferation cycle and apoptosis of pancreatic cancer. Western blot analysis detected changes in apoptosis, migration, and other pathway proteins in SW1990 cells after transfection. Results: ABCA12 is highly expressed in pancreatic cancer tissues and cells. After ABCA12 was knocked down, the proliferation, invasion, and migration of SW1990 cells were significantly reduced, and apoptosis was increased. The changes in pathway proteins suggested that ABCA12 may regulate the progression of pancreatic cancer through the AKT pathway. Conclusion: We found that ABCA12 is differentially expressed in pancreatic tissues and cells. ABCA12 can also affect the biological behavior of pancreatic cancer cells effectively, which may serve as a new target for pancreatic cancer diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Background: Modern lifestyles mean that people are more likely to suffer from some form of cancer. As anticancer peptides can effectively kill cancer cells and play an important role in fighting cancer, they have been a subject of increasing research interest. Methods: This study presents a useful tool to identify the anticancer peptides based on a multi-kernel CNN and attention model, called ACP-MCAM. This model can automatically learn adaptive embedding and the context sequence features of ACP. In addition, to obtain better interpretability and integrity, we visualized the model. Results: Benchmarking comparison shows that ACP-MCAM significantly outperforms several state-of-the-art models. Different encoding schemes have different impacts on the performance of the model. We also studied tmethod parameter optimization. Conclusion: The ACP-MCAM can integrate multi-kernel CNN and self-attention mechanism, which outperforms the previous model in identifying anticancer peptides. It is expected that the work will provide new research ideas for anticancer peptide prediction in the future. In addition, this work will promote the development of the interdisciplinary field of artificial intelligence and biomedicine. [ABSTRACT FROM AUTHOR]

Background: Inhibin A (INHBA), a member of the TGF - β superfamily, has been shown to be differentially expressed in various cancer types and is associated with prognosis. However, its role in cervical cancer remains unclear. Methods: We aimed to demonstrate the relationship between INHBA expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated INHBA expression in cervical cancer using the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750 datasets. Enrichment analysis of INHBA was performed using the R package "clusterProfiler." We analyzed the association between immune infiltration level and INHBA expression in cervical cancer using the single-sample gene set enrichment analysis (ssGSEA) method by the R package GSVA. We explored the association between INHBA expression and prognosis using the R package "survival". Results: Pan-cancer data analysis showed that INHBA expression was elevated in 19 tumor types, including cervical cancer. We further confirmed that INHBA expression was higher in cervical cancer samples from GEO database and cervical cancer cell lines than in normal cervical cells. Survival prognosis analysis indicated that higher INHBA expression was significantly associated with reduced Overall Survival (p = 0.001), disease Specific Survival (p = 0.006), and Progression Free Interval (p = 0.001) in cervical cancer and poorer prognosis in other tumors. GSEA and infiltration analysis showed that INHBA expression was significantly associated with tumor progression and some types of immune infiltrating cells. Conclusion: INHBA was highly expressed in cervical cancer and was significantly associated with poor prognosis. Meanwhile, it was correlated with immune cell infiltration and could be used as a promising prognostic target for cervical cancer. [ABSTRACT FROM AUTHOR]

Combination therapies proved to be a valuable strategy in the fight against cancer, thanks to their increased efficacy in inducing tumor cell death and in reducing tumor growth, metastatic potential, and the risk of developing drug resistance. The identification of effective combinations of drug targets generally relies on costly and time consuming processes based on in vitro experiments. Here, we present a novel computational approach that, by integrating dynamic fuzzy modeling with multi-objective optimization, allows to efficiently identify novel combination cancer therapies, with a relevant saving in working time and costs. We tested this approach on a model of oncogenic K-ras cancer cells characterized by a marked Warburg effect. The computational approach was validated by its capability in finding out therapies already known in the literature for this type of cancer cell. More importantly, our results show that this method can suggest potential therapies consisting in a small number of molecular targets. In the model of oncogenic K-ras cancer cells, for instance, we identified combination of up to three targets, which affect different cellular pathways that are crucial for cancer proliferation and survival. [ABSTRACT FROM AUTHOR]

Lipid species are known to have various biological functions owing to their structural differences, and each of them possesses a specific role to play depending upon their location and distribution in the cell. Some of these lipids interact with proteins on the cell membrane and acts as second messengers. The level of lipid mediators is generally maintained in the cell by feedback mechanisms; however, their improper degradation or enhanced production leads to their accumulation in the tumor microenvironment and disturbs the homeostasis of the cell. Platelet activating factor (PAF) is a known phospholipid mediator secreted upon immunological challenges by platelets, neutrophils, basophils, and macrophages. PAF, as a potent inflammatory molecule, is well studied, and its role in various cancers and cardiovascular diseases has also been investigated. Interestingly, increased levels of PAF have been found in the blood plasma of smokers, and breast cancer cells have shown the accumulation of PAF in presence of cigarette smoke extract. This accumulation was found to increase tumor cell motility that in turn could promote metastasis. Beyond this, however, the effect of PAF on tumorigenesis has not yet been well explored. Here, we show that the continuous exposure of 3D breast acinar cultures to PAF resulted in the activation of various oncogenic signaling pathways leading to transformation. We also found that the presence of PAF in the micro-environment increased the expression of PAF receptor (PAF-R), which corroborated with the higher expression of PAF-R detected in some epithelial cancers, as per literature. Thus, this study impresses on the fact that the presence of PAF alters the cellular microenvironment and eventually triggers irreversible effects that can cumulatively lead to transformation. [ABSTRACT FROM AUTHOR]

Cancer is characterized by dysregulation at multiple levels, such as gene transcription. Enhancers are well-studied transcription regulators that can enhance target transcripts through DNA loop formation mediated by chromosome folding. The gain or loss of the interaction between an enhancer and its target gene has a critical effect on gene expression. In this study, we analyzed GRO-seq data to identify active enhancers from seven common cancer cell lines and studied the function of these enhancers across multiple cancer types. By constructing an "enhancer effect score" (EES), we found a significant correlation between EES and tumor-infiltrating lymphocytes (TILs) in prostate cancer. Further analysis revealed that androgen receptor (AR) plays an important role in regulating the immune checkpoint gene PVR via its enhancer. These results suggest that AR contributes to prostate cancer aggressiveness by promoting cancer cell immune evasion. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide despite the availability of diverse treatment strategies. Much research progress has been made regarding immunotherapy but the effects remain unsatisfactory, highlighting the urgent need for novel immune-related therapy targets. In recent years, more and more studies have pointed out the associations between certain transmembrane (TMEM) family proteins and tumor progression, but the role of TMEM205 remains unclear. In this study, we analyzed the RNA-seq and clinical data of 371 patients from The Cancer Genome Atlas (TCGA) and found significant differential expression of TMEM205 between normal and tumor tissues (P < 0.001). Low TMEM205 expression was also found to be independently associated with poor overall survival (OS; p = 0.032) and poor disease-specific survival (DSS; p = 0.002) in multivariate Cox regression analyses. RNA-seq and clinical data from hepatocellular carcinoma patients in the International Cancer Genome Consortium (ICGC) also showed significant differential expression of TMEM205 (P < 0.001) and association between low TMEM205 expression and poor survival (P < 0.001). We also used the Estimate the Proportion of Immune and Cancer cells (EPIC) tool to estimate the proportions of various immune cells in the tumor tissues. A correlation analysis was conducted, and TMEM205 expression in tumor tissues was found to be significantly associated with the proportion of macrophages (Pearson r = 0.45, p < 0.0001). A negative correlation was found between TMEM205 expression and M2 macrophage markers (CD163 , EGR2 , and MS4A4A) and between TMEM205 expression and regulatory T cell (Treg) markers (CCR8 , STAT5B , and IL2RA), while a positive correlation was found between TMEM205 expression and the proportion of CD8+ T cells (Pearson r = 0.26, p < 0.0001). In conclusion, TMEM205 might improve HCC patients' prognosis by reducing the levels of immunosuppressive cells (M2 macrophages and Tregs) and facilitating the infiltration of cytotoxic T cells into the tumor microenvironment. Therefore, TMEM205 has potential as a prognostic biomarker and immunotherapy agent in combination therapy regimens for HCC. [ABSTRACT FROM AUTHOR]

Cisplatin has been widely used in the treatment of a various types of cancers including triple-negative breast cancer (TNBC) by damaging DNA and inducing apoptosis. However, its anti-cancer effects are often limited due to chemo-resistance, which is one of the main reasons causing cancer relapse and metastasis. To overcome resistance, cisplatin is often used in combination with other drugs or molecules. Our study found that the targeted inhibition of miR-221/222 in MDA-MB-231 cells promoted cisplatin-induced cell apoptosis, and increased the cell sensitivity to cisplatin in vitro. Much higher expression levels of miR-221/222 were detected in the cisplatin-resistant MDA-MB-231 cells and in cisplatin-resistant breast cancer patients. The combination chemotherapy of cisplatin with anti-miR-221/222 showed much higher efficiency in suppressing tumor growth in the mice transplanted with MDA-MB-231 cells. In addition, anti-miR-221 and anti-miR-222 showed synergetic effects on improving sensitivity to cisplatin in MDA-MB-231 cells. Suppression of SOCS1-STAT3-Bcl-2 pathway and activation of p53-Pten signaling both contribute to anti-miR-221/222-induced sensitivity to cisplatin in MDA-MB-231 cells. These findings suggest the potential of a novel approach for the combination chemotherapy of cisplatin with small non-coding RNA in treatment of human TNBC. [ABSTRACT FROM AUTHOR]

Finally, the Authors explored the role of secreted, circulating miRNAs in cachexia, not only as potential prognostic and diagnostic tools, but also as critical modulators of apoptosis associated to muscle wasting. MicroRNAs, muscle, muscle wasting (atrophy), cancer, extracellular vesicles, cachexia Keywords: microRNAs; muscle; muscle wasting (atrophy); cancer; extracellular vesicles; cachexia EN microRNAs muscle muscle wasting (atrophy) cancer extracellular vesicles cachexia 1 2 2 05/17/22 20220513 NES 220513 MicroRNAs (miRNAs) are small non-coding RNA molecules that have gathered importance over the last decade as critical regulators of several biological processes, including differentiation, cell cycle regulation, aging and development ([2]). [Extracted from the article]

The emerging single-cell RNA-Seq (scRNA-Seq) technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to interpret the complexity in scRNA-Seq data is just as challenging. Here, we review current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces. [ABSTRACT FROM AUTHOR]

Tumorigenesis is a multi-step process, involving the acquisition of multiple oncogenic mutations that transform cells, resulting in systemic dysregulation that enables proliferation, invasion, and other cancer hallmarks. The goal of precision medicine is to identify therapeutically-actionable mutations from large-scale omic datasets. However, the multiplicity of oncogenes required for transformation, known as oncogenic collaboration, makes assigning effective treatments difficult. Motivated by this observation, we propose a new type of oncogenic collaboration where mutations in genes that interact with an oncogene may contribute to the oncogene's deleterious potential, a new genomic feature that we term "surrogate oncogenes." Surrogate oncogenes are representatives of these mutated subnetworks that interact with oncogenes. By mapping mutations to a protein-protein interaction network, we determine the significance of the observed distribution using permutation-based methods. For a panel of 38 breast cancer cell lines, we identified a significant number of surrogate oncogenes in known oncogenes such as BRCA1 and ESR1, lending credence to this approach. In addition, using Random Forest Classifiers, we show that these significant surrogate oncogenes predict drug sensitivity for 74 drugs in the breast cancer cell lines with a mean error rate of 30.9%. Additionally, we show that surrogate oncogenes are predictive of survival in patients. The surrogate oncogene framework incorporates unique or rare mutations from a single sample, and therefore has the potential to integrate patient-unique mutations into drug sensitivity predictions, suggesting a new direction in precision medicine and drug development. Additionally, we show the prevalence of significant surrogate oncogenes in multiple cancers from The Cancer Genome Atlas, suggesting that surrogate oncogenes may be a useful genomic feature for guiding pancancer analyses and assigning therapies across many tissue types. [ABSTRACT FROM AUTHOR]

Exosomes are membranous vesicles containing various biomolecules including lncRNAs which are involved in cellular communication and are secreted from many cells including cancer cells. In our study, investigated the exosomal GAS5 and lincRNA-p21 lncRNA levels in urine samples from 30 patients with prostate cancer (PCa) and 49 patients with benign prostatic hyperplasia. Quantification of lncRNA molecules was performed by real-time PCR. We observed a significant difference in the exosomal lincRNA-p21 levels between PCa and BPH patients whereas the GAS5 levels did not reveal a difference. Our data suggest that the discriminative potential of exosomal lincRNA-p21 levels may help to improve the diagnostic prediction of the malignant state for patients with PCa. [ABSTRACT FROM AUTHOR]

Recent advance of sequencing technology has revealed genetic alterations in colorectal cancer (CRC). The biological function of recurrently mutated genes has been intensively investigated through mouse genetic models and CRC cell lines. Although these experimental models may not fully reflect biological traits of human intestinal epithelium, they provided insights into the understanding of intestinal stem cell self-renewal, leading to the development of novel human intestinal organoid culture system. Intestinal organoid culture enabled to expand normal or tumor epithelial cells in vitro retaining their stem cell selfrenewal and multiple differentiation. Gene manipulation of these cultured cells may provide an attractive tool for investigating genetic events involved in colorectal carcinogenesis. [ABSTRACT FROM AUTHOR]