Cancer Prognostic Markers Research Articles

Whole transcriptome sequencing identifies a competitive endogenous RNA network that regulates the immunity of bladder cancer

Several types of non-coding RNAs such as circRNAs, lncRNAs, and miRNAs have been identified to regulate mRNAs through the mechanism known as the competitive endogenous RNA (ceRNA) network. To explore the role of the ceRNA regulatory network in the immune microenvironment of bladder cancer, whole-transcriptome sequencing of bladder tumor and its peritumoral tissues from 38 bladder cancer patients, with a total of 63 samples, was performed to screen differentially expressed circ-, lnc-, mi-, and mRNAs to construct a circ/lnc-mi-mRNA regulatory network with pruning algorithms. We excavated a key immune-related gene BDNF to build the final ceRNA network as hsa-miR-107 sponged by hsa-circ-000211, AC108488.1, and LINC00163. Finally, a meta-analysis of 7 public datasets demonstrated that low expression of BDNF and high expression of hsa-miR-107 were associated with longer survival. Our study identified a ceRNA regulatory network as a potentially new prognostic marker and molecular therapeutic target of bladder cancer.

Contribution of sphingomyelin phosphodiesterase acid-like 3B to the proliferation, migration, and invasion of ovarian cancer cells.

Cancer has the highest mortality rate among gynecological cancers and poses a serious threat to women's lives. However, the treatment options for ovarian cancer are still limited, and exploring effective targeted biomarkers is particularly important for predicting and treating ovarian cancer. Therefore, it is necessary to explore the molecular mechanisms of the occurrence and development of ovarian cancer. This investigation encompassed the analysis of gene expression profiles, measurement of transcription levels of potential target genes in peripheral blood samples from ovarian cancer patients and characterization of the ovarian cancer-related secretory protein sphingomyelin phosphodiesterase acid-like 3B (SMPDL3B). Through bioinformatics analysis, potential target genes were identified, and their association with overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients was assessed utilizing relevant databases. Subsequently, differences in target gene expression in ovarian cancer tissue samples were validated through protein blotting and quantitative real-time PCR (qRT-qPCR). Cell proliferation assays using the cell count kit-8 (CCK-8) method, as well as transwell chamber assay and pre coated matrix gel chamber assay were employed to elucidate the role of SMPDL3B in ovarian cancer cell migration and invasion. This study revealed a substantial upregulation of SMPDL3B in the serum of ovarian cancer patients, correlating with an unfavorable prognosis. High SMPDL3B expression was linked not only to increased proliferation of ovarian cancer cells, but also enhanced migration and invasion. Remarkably, the knockdown the human alkaline ceramidase 2 (ACER2) gene in cancer cells with heightened SMPDL3B expression significantly inhibited cell proliferation, migration, and invasion induced by SMPDL3B activation (P<0.05), highlighting the functional interplay between ACER2 and SMPDL3B in ovarian cancer. In summary, this study proposes SMPDL3B as a prognostic marker for ovarian cancer, with implications for potential therapeutic intervention targeting the ACER2-SMPDL3B axis.

Long-Noncoding-RNA HOTAIR Upregulation is Associated with Poor Breast Cancer Outcome: A Systematic Review and Meta Analysis.

Breast cancer is the most frequent cancer among women worldwide with significant disproportionate mortality rates in developing countries. Although clinical management of breast cancer has been immensely improved, refinement in the prognostic and recurrent markers is still needed. Long non-coding RNAs (lncRNA) HOTAIR has recently been associated with poor outcome and is potentially used as a prognostic marker in breast cancer. We comprehensively reviewed studies evaluating lncRNA HOTAIR in association with overall and disease-free survivals in breast cancers. Systematic searches were performed in Pubmed, ProQuest, ScienceDirect, Scopus, Google Scholar, Semantic Scholar, Springer, Nature, Sage Journals, and Wiley databases using combination keywords "long non-coding RNA," "lncRNA," "HOX transcript antisense RNA," "HOTAIR," "breast can-cer," "carcinoma mammae," "prognosis," and "survival." Risk of bias score was used to assess quality of studies, I2 test was conducted to assess heterogeneity. Meta-analysis was performed to compare HOTAIR expression with breast cancer survival rates using STATA v.17 software. Of the total 1,504 screened studies, seven studies were included in the meta-analysis involving 533 patients. High expression of HOTAIR was associated with poor survival rates (pooled HR: 1.69; 95%CI: 1.11-2.59; p=0.015), shorter overall survival (OS) (pooled HR: 1.33; 95%CI: 0.78-2.26; p=0.455), poor disease-free survival (DFS) (pooled HR: 2.40; 95%CI: 1.63-3.53; p<0.001), poor distant metastatic-free survival (MFS) (HR: 1.75; 95%CI: 1.13-2.71; p=0.012). In addition, overexpression of HOTAIR was associated with positive lymph node infiltration (pooled OR: 2.38; 95%CI: 0.53-10.69; p=0.26) and ductal type cancer (pooled OR: 3.27; 95%CI: 1.15-9.30; p=0.03). Upregulation of lncRNA HOTAIR is associated with worse DFS aand MFS that can potentially be used as a prognostic marker in breast cancer patients.

Immunochemistry-based quantification of tumor-infiltrating lymphocytes and immunoscore as prognostic biomarkers in bladder cancer

BackgroundTumor-infiltrating lymphocytes (TILs) and the derived immunoscore (IS) have gained considerable attention over the last decade as prognostic markers in many solid cancers. However, in bladder cancer (BC), their prognostic value is not clearly established.MethodsThe present study aimed to quantify the TILs rates in BC, assess the derived immunoscore, and investigate their prognostic value. An immunochemistry-based quantification of the different subtypes of TILS was performed on paraffin-embedded blocks from patients with invasive urothelial carcinoma of the bladder. We have assessed the rates of TILs, respectively, on peri-tumoral (PT) and intra-tumoral (IT) areas and calculated for each case the corresponding IS which is the index: CD8+/CD3+ TILs. The IS was then classified as low (I0, I1) or high (I2, I3, I4). We included 30 cases in the analysis.ResultsThe median age of patients was 65 years with a sex ratio of 9. TILs densities and distribution were significantly variable between IT and PT areas CD3+ (p = 0.03) and CD8+ (p = 0.004) with the highest rates on the PT areas. In univariate analysis, a low density of CD8+ TILs was significantly associated with an advanced age (p = 0.05), with the presence of lympho-vascular invasion (p = 0.02) and with the absence of specific histological subtype (p = 0.05). A low immunoscore was significantly associated with the presence of lympho-vascular invasion (p = 0.004). No significant association was found between TILs subpopulations, the IS, and the other clinicopathological and survival data. The overall survival (OS) and disease-free survival (DFS) medians were slightly superior in highly T (CD3+/CD8+)-cell infiltrated tumors as well as tumors with a high IS densities. However, the univariate analysis showed that TILs and immunoscore did not impact overall survival (OS) and disease-free survival (DFS).ConclusionTILs and immunoscore might be effective prognostic tools in BC. However, standardized quantification methods and further investigation on larger samples are highly recommended to definitively attest the prognostic value of TILs and IS in BC.

DNA Ploidy as a Potential Adjunct Prognostic Marker of Low-Risk Prostate Cancer Progression after Radical Prostatectomy.

Post prostatectomy PSA kinetics and General Grade Groups (GGG) are the strongest prognostic markers of biochemical recurrence (BCR) and prostate cancer (PCa)-specific mortality after radical prostatectomy. Despite having low-risk PCa, some patients will experience BCR, for some, clinically significant BCR. There is a need for an objective prognostic marker at the time of prostatectomy to improve risk stratification within this population. In this study, we investigated the prognostic potential of DNA ploidy. Prostatectomy samples from 97 patients with GGG1 and GGG2 with a low-risk CAPRA-S score were included in this study. PCa tissue with the worst Gleason pattern underwent tissue disaggregation, cell isolation and staining with a DNA stoichiometric stain. Using image cytometry, DNA ploidy was measured and a Ploidy Score (PS) was generated. Among the 97 patients, 79 had no BCR, 18 experienced BCR, of which 14 had a PSA doubling time (PSA-DT) >1 year (low-risk group) and 4 had a PSA-DT of <1 year (high-risk group). Using Logistic regression analysis, only pathological T stage (pT) and PS independently predicted BCR with PS being the most significant (p = 0.001). The number of aneuploid cells was significantly higher in the high-risk group compared to the other groups (p = 1.7x10-11). PS combined with GGG diagnosis further stratified risk groups of biochemical recurrence free survival within CAPRA-S low-risk cohort. DNA ploidy is an independent prognostic marker of BCR in low-risk PCa after radical prostatectomy, which could early on identify potentially aggressive PCa recurrences and introduce a more personalized approach to salvage treatments.

Abstract 3486: Triple hormone receptor signatures as novel prognostic markers in breast cancer

Abstract Background: Tumor phenotype across various cancers, including breast cancer, is predominantly shaped by a synergy between genomic alterations and the cell-of-origin from which the tumor originates. These elements collectively influence crucial aspects like tumor aggressiveness, treatment response, and patient prognosis. While existing research highlights that the role of cell-of-origin in shaping the molecular architecture of breast cancer, leveraging this information for actionable clinical insights has proven challenging. Here, we introduce two robust models leveraging cellular ancestry signatures of breast luminal cells to improve patient stratification and outcome prediction. Methods: In this study, we developed a unique gene signature anchored in the expression levels of triple hormone receptors (THR)—namely androgen (AR), estrogen (ER), and vitamin D (VDR)—in breast cancer cells. Building on this, we formulated two distinct mRNA markers, THR-50 and THR-70, aimed at categorizing breast tumors based on their THR expression profiles. These markers were rigorously validated across 65 independent breast cancer studies, involving a total of 6,679 patients, utilizing Kaplan-Meier survival curves, Cox proportional hazards models, and unsupervised clustering analyses. Results: Our findings indicate that both THR-50 and THR-70 are robustly associated with overall survival and recurrence-free survival in breast cancer patients across all datasets evaluated. Importantly, these THR signatures demonstrate broad applicability across various breast cancer subtypes, grades, and treatment phases—unlike existing prognostic markers that tend to be subtype-specific. Additionally, the THR signatures have revealed four unique patient clusters with divergent survival outcomes, three of which are ER-positive and one is ER-negative. Additionally, we developed an immune-based signature (i20) which can further categorize patients within the ER-negative cluster into two subgroups: one with a highly favorable prognosis, comparable to the ER-positive subtypes, and another that is characterized by exceedingly poor survival outcomes. Conclusion: The THR-based cellular ancestry signatures open a new avenue in understanding the intricacies of breast cancer biology. These signatures offer a robust and stable framework for developing other prognostic markers, thus providing an enhanced stratification of existing breast cancer categories as well as creating new classifications with more distinct survival estimates. Citation Format: Mohamed Omar, J. Chuck Harrell, Rulla M. Tamimi, Luigi Marchionni, Tan Ince. Triple hormone receptor signatures as novel prognostic markers in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3486.

Abstract 4915: Identification and validation of novel prognostic genetic markers in HER2-negative advanced gastric cancer (AGC) by artificial intelligence (AI) deep learning and machine learning algorithm

Abstract Introduction: Despite advances in anticancer treatments, there has been urgent need to identify novel prognostic markers for HER2-negative AGC. We propose AI based deep learning and machine learning pipeline to explore genetic markers that predict patient response to chemotherapy in HER2-negative AGC. Methods: We retrospectively assessed 179 stage IV HER2-negative AGC patients who have been treated with first-line chemotherapy in Yonsei Cancer Center, Korea between 2015 and 2021. In-house targeted sequencing panel data (CancerSCANTM and CancerMaster) were used to identify candidate prognostic markers. DeepSurv was mainly used to analyze the progression-free survival (PFS), which is a deep learning algorithm that can investigate prognostic roles. The SHapley Additive exPlanations (SHAP) method was applied to open the deep learning models’ black-box and calculate the importance ranking of gene features. Machine learning models-random survival forest, elastic-net, and lasso-were also investigated to identify potentially meaningful gene variants. To rank the gene features, we calculated variable importance (VIMP) for random survival forest, and penalized regression coefficients for elastic-net and lasso. All deep learning and machine learning models were trained using 5-folds cross-validation in 1,000 iterations of re-sampling bootstrapping with hyperparameter tuning by grid search. To classify responder or non-responder related genetic markers to chemotherapy, we used the signs of averaged penalize coefficients obtained from elastic-net and lasso. Based on the median linear predictor with candidate gene features, patients were classified into high-risk and low-risk group. Results: A total of 7,824 common variants were analyzed and 20 prognostic genetic markers were identified based on the top average values of SHAP, VIMP, and penalized regression coefficients. The top 10 non-responder genetic markers are included as follows: PARP4(p.S873N), CHUK(p.V268I), BARD1(359_365del), CREBBP(p.Y1125F), BARD1(p.P24S), PHLPP2(p.R1312Q), FAT3(p.Q3375R), CASP5(p.T106A), PHLPP2(p.I544V), and PTCH2(p.T988M). Otherwise, the top 10 responder genetic markers are defined as follows: IL7R(p.I66T), NOTCH4(L16delinsLL), FGFR3, BCL2A1(p.G82D), ZNF217(p.T548I), BRCA1(p.K1183R), FANCA(p.A412V), ADGRA2, CDKN2B, and FANCM(p.S175F). The high-risk group had worse PFS compared with low-risk group (median PFS 4.1 vs. 9.1 months; P-value &amp;lt;0.0001). Conclusion: This study showed the potential of AI deep learning and machine learning pipeline that employs an innovate prognostic genetic markers for HER2-negative AGC. Current ongoing analyses of larger cohort with more comprehensive clinical data will be presented. Citation Format: Sejung Park, Seok-Jae Heo, Choong-Kun Lee, Yaeji Lee, Woo Sun Kwon, Jingmin Che, Minseok Kim, Hyun Cheol Chung, Sun Young Rha. Identification and validation of novel prognostic genetic markers in HER2-negative advanced gastric cancer (AGC) by artificial intelligence (AI) deep learning and machine learning algorithm [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4915.

Abstract 650: Pim3 kinase is a poor prognostic marker and novel molecular target for triple negative breast cancer

Abstract Triple-negative Breast cancer (TNBC) is characterized by the absence of ER, PR, and HER-2 receptors and is associated with poor prognosis, early relapse, and distant metastasis. In neoadjuvant setting, most patients (~50-70%) with TNBC do not achieve complete remission. Currently, there is no effective targeted therapy for TNBC patients. Therefore, identifying novel molecular targets and developing alternative therapeutic strategies are urgently needed. PIM3 is a serine/threonine kinase and is upregulated in leukemia and various solid cancers. Although PIM1 has been shown to play a critical role in cell proliferation in cMyc-enriched TNBC tumors, the role of PIM3 in TNBC is not known. To determine the clinical significance of PIM3 in TNBC patient prognosis and progression, we performed a Kaplan-Meier analysis in the TCGA TNBC patient database. We found that PIM3 expression is significantly associated with shorter patient survival in TNBC patients (n=77, p=0.0088). PIM3 protein is highly expressed in TNBC cells compared to normal breast epithelium and other ER+ and HER2+ breast cancer subtypes. Inhibition of PIM3 by siRNA significantly suppressed TNBC cell proliferation, migration, and invasion of TNBC cells including MDA-MB-231, MDA-MB-436, and BT20 cells. Lenti-based PIM3 overexpression induced TNBC cell proliferation, invasion, and migration. Non-biased reverse phase protein array (RPPA) assay and Western blot analysis showed that PIM3 inhibition markedly reduced the expression of EF2 Kinase protein, and we found it to be associated with shorter patient survival and poor prognosis. Immunoprecipitation of PIM3 indicated that it forms a heterodimer with EF2K whose inhibition by siRNA also suppressed TNBC cell proliferation, migration, invasion, and tumor growth. Furthermore, PIM3 inhibition by siRNA significantly enhanced the antiproliferative effect of Doxorubicin, which is one of the first-line chemotherapeutics used in patients. Moreover, in vivo therapeutic delivery of PIM3 siRNA loaded albumin nanoparticles (ALNPs-PIM3 siRNA) markedly delayed tumor growth of two different TNBC tumor xenograft models (MDA-MB-231 and MDA-MB-436) in mice. Analysis of tumors by IHC after 4 weeks of treatment demonstrated that ALNP-PIM3 siRNA treatment led to inhibition of intra-tumoral proliferation and induction of apoptosis. Currently, we are conducting an in vivo study in TNBC tumor models by combining ALNP-PIM3 siRNA therapy with doxorubicin. Overall, our studies suggest that PIM3 is a marker for poor patient survival that drives TNBC tumor growth and progression and a novel potential molecular target in TNBC. Citation Format: Pinar Atalay, Goknur Kara, Rumeysa Ozyurt, Nermin Kahraman, Bulent Ozpolat. Pim3 kinase is a poor prognostic marker and novel molecular target for triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 650.

Abstract 3067: SLC7A5/LAT1 promotes the Warburg Effect for TNBC progression through Trp/QPRT/NAD+ pathway

Abstract SLC7A5/LAT1 is a cross-membrane transporter that functions in uptake of large neutral amino acids into cells. Many pathological studies have shown that LAT1 is highly expressed in cancer tissue from various origins such as lung, biliary tract, breast, prostate, bone, and their metastatic legions. High LAT1 expression has been recognized as a significant prognostic marker in various cancers. Our TCGA data analysis showed that the expression level of LAT1 is higher in TNBC tumors compared with normal breast tissues. The higher expression level of LAT1 is linked with poor overall and progression-free survival. Dysregulation of amino acid transporters lead to metabolic reprogramming, which changes intracellular amino acid levels, contributing to the pathogenesis of cancer. However, it remains elusive whether and how LAT1 re-wires the cellular metabolic programs to promote TNBC tumor proliferation. In this study, we showed that inhibition of SLC7A5/LAT1 significantly reduced TNBC cell proliferation, viability, migration capability while promoting apoptosis. Mechanistically, we found significant positive correlations of LAT1 with PKM2 and LDHA in breast cancer tissues, which are key enzymes in mediating glycolysis and lactate fermentation or the Warburg Effect. Knock down LAT1 via siRNA decreased the expression levels of p-PKM2 and p-LDHA in TNBC cells. Tryptophan, a major substrate amino acid transported into cytosol by LAT1, is the precursor for the de novo synthesis of nicotinamide adenine dinucleotide (NAD+). The enzyme quinolinic acid phosphoribosyltransferase (QPRT) catalyzes the conversion from quinolinate, a product of tryptophan degradation, to NAD+. We showed LAT1 inhibition reduced the expression level of QPRT, cytosolic NAD+/NADH ratio as well as lactate production. Addition of L-Tryptophan increased the levels of p-PKM2 and p-LDHA while knockdown of LAT1 reversed tryptophan-mediated increase of PKM2 and LDHA activities, suggesting that LAT1 may regulate PKM2/LDHA through Trp/QPRT/NAD+ pathway for promoting the Warburg Effect. Additionally, we found upregulations of SLC7A5/LAT1, p-PKM2 and p-LDHA in doxorubicin-resistant cells and PDX mouse model compared with their corresponding controls. Collectively, these results provide evidence that overexpression of LAT1 in TNBC drives cancer progression and drug resistance by reinforcing the Warburg Effect, suggesting LAT1 as a promising therapeutic target for addressing TNBC. Our ongoing work will evaluate whether inhibiting LAT1 genetically or pharmacologically reduces xenograft tumor growth and enhances the sensitivities of TNBC resistant cells to chemotherapy in vivo. Our investigation will elucidate the underlying mechanisms involved in these processes. Citation Format: Margot Y. Fedoroff, Lei Zhao, Leili Saeednejad Zanjani, Jun He. SLC7A5/LAT1 promotes the Warburg Effect for TNBC progression through Trp/QPRT/NAD+ pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3067.

Abstract 2273: Development of a prognostic biomarker for ovarian cancer based on a high-resolution digital pathology platform for spatial statistical analysis of platelets and blood vessels

Abstract Purpose: A third of ovarian cancer patients have elevated platelet counts that are associated with poor prognosis. However, the exact mechanism by which platelets preferentially extravasate into tumor microenvironment is unknown, partly owing to lack of effective tools that can accurately segment and measure platelet counts found in tumor tissues. In this study, we developed a high-resolution digital pathology (DP) platform with whole tissue confocal imaging and deep learning model that can be used to automatically segment out platelets and blood vessels to perform spatial statistics (SA) of platelets with high precision and consistency. We utilized our SADP platform to study an interaction between tumor secreted SDF-1 and CXCR4 on platelets which initiates platelet chemotaxis towards tumor microenvironment. Methods: A deep learning algorithm to accurately segment out platelets was developed based on the U-Net structure using our original datasets from the murine ovarian cancer model. Tumor-bearing mice were injected with 5 mg/kg of Plerixafor, a CXCR4 inhibitor, daily for 4 weeks. Then, tumor nodules were resected, stained with CD41a and CD31 antibodies, and imaged using a whole slide confocal microscopy. We performed manual annotation of these images to generate the mask dataset and performed further data augmentation to increase the diversity of datasets. We trained our model using 85% of these images and performed validation using the remaining 15%. Results: Using our SADP platform, the validation dataset achieved pixel-wise accuracy of 98.8%. A receiver operating characteristic (ROC) curve demonstrated an area under the ROC curve (AUC) of 0.99 with high sensitivity and specificity. Intersection over union (IoU) score of 0.765 was obtained. A statistically significant (p=0.0467), 7.03% reduction in the platelet density was shown in the Plerixafor-treated mouse ovarian tumor tissues (n=8) compared to the control tumor tissues (n=9). We also found that platelets are spatially concentrated near blood vessels in the control tumor tissues compared to the Plerixafor-treated tumor tissues (p=0.0377). Conclusions: We developed a SADP platform to segment and quantitate tens of thousands of platelets from whole slide mouse ovarian cancer tissues automatically with high accuracy and consistency and incorporated spatial statistics to understand their spatial relationships and patterns that would not be apparent in non-spatial analyses. Applying the SADP platform, we demonstrated that treatment with Plerixafor leads to overall reduction in platelet infiltration within ovarian murine tumors. Our ongoing effort is to utilize our SADP platform on human tumor tissue images from a whole slide digital scanner to further characterize spatial distribution of platelets as a potential prognostic marker for ovarian cancer. Citation Format: Ju Young Ahn, Wendolyn Carlos-Alcalde, Matthew Vasquez, Min Soon Cho, Vahid Afshar-Kharghan, Stephen T. Wong. Development of a prognostic biomarker for ovarian cancer based on a high-resolution digital pathology platform for spatial statistical analysis of platelets and blood vessels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2273.

Impact of RRP1B Variants on the Phenotype, Progression, and Metastasis of Cervical Cancer.

Metastasis is a key determinant of cancer progression, influenced significantly by genetic mechanisms. RRP1B, primarily a nucleolar protein, emerges as a suppressor of metastasis, forming alliances with various cellular components and modulating gene expression. This study investigates the involvement of the ribosomal RNA processing 1 homolog B (RRP1B) gene in metastasis regulation in cervical cancer. Through a comprehensive analysis of 172 cervical cancer patients, we evaluated five RRP1B single nucleotide polymorphisms (SNPs) (rs2838342, rs7276633, rs2051407, rs9306160, and rs762400) for their associations with clinicopathological features and survival outcomes. Significant associations were observed between specific genetic variants and clinicopathological parameters. Notably, the A allele of rs2838342 was associated with reduced odds of advanced tumor size, worse prognosis, and, preliminarily, distant metastasis, while the T allele of rs7276633 correlated with a decreased risk of higher tumor size and worse prognosis. Additionally, the C allele of rs2051407 demonstrated protective effects against larger tumors, metastasis, and adverse prognosis. The rs9306160 C allele exhibited a protective effect against metastasis. The rs762400 G allele was significant for reduced tumor size and metastasis risk. Furthermore, the rs2838342 A allele, rs7276633 T allele, rs2051407 C allele, and rs762400 G allele were associated with improved overall survival, demonstrating their potential significance in predicting prognoses in cervical cancer. Linkage disequilibrium and haplotypes analysis enabled us to evaluate the collective effect of the analyzed SNPs, which was in line with the results of allelic models. Our findings underscore the clinical relevance of RRP1B SNPs as prognostic markers in cervical cancer, shedding light on the intricate interplay between genetic factors and disease-progression dynamics. This research provides critical insights for future investigations and underscores the importance of incorporating RRP1B SNP detection into prognostic-assessment tools for accurate prediction of disease outcomes in cervical cancer.

Abstract 4892: MicroRNA signature and telomere genes in kidney cancer survival

Abstract Introduction: Kidney cancer ranks among the top 10 most prevalent cancers in the United States, clear cell renal cell carcinoma (ccRCC) has the worst disease specific survival histology. MicroRNAs (miRNAs) have emerged as potential prognostic indicators in various cancers, including kidney cancers. Telomerase, a biomarker associated with uncontrolled cancer cell growth, plays a crucial role in the human kidney cortex's telomere shortening over time. However, the link between miRNAs and telomeres in kidney cancer survival remains underexplored. Our study aims to uncover a miRNA signature capable of predicting 5-year survival in ccRCC patients and to investigate the biological relevance of this signature, particularly its shared pathway enrichment mechanisms with telomere genes. Methods: We extracted miRNA expression profiles from The Cancer Genome Atlas database, comprising 166 patients with ccRCC. To identify a robust miRNA signature predicting 5-year survival in ccRCC, we established an Evolutionary Kidney Survival Estimator (EKSE) using an optimal feature selection algorithm and support vector regression. Additionally, we conducted bioinformatics analyses to uncover common biological pathways between miRNAs and telomere genes using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) categories, encompassing biological processes, molecular functions, and cellular components. Results: EKSE identified a robust signature consisting of 37 miRNAs, achieving a mean correlation coefficient and mean absolute error of 0.82±0.01 and 0.65±0.18, respectively between actual and estimated survival times. The top 10 ranked miRNAs in the signature, including hsa-miR-26a-1-3p, hsa-miR-28-5p, hsa-miR-3913-5p, hsa-miR-3170, hsa-miR-148a-5p, hsa-miR-671-3p, hsa-miR-224-3p, hsa-miR-10a-5p, hsa-miR-29b-1-5p, and hsa-miR-106b-5p, also showed promise in diagnosing ccRCC with AUC values ranging from 0.56 to 0.91. Furthermore, bioinformatics analysis revealed that the miRNA signature targeted well known telomere-associated genes such as TERT, DKC1, CTC1, and RTEL1. Notably, miRNA signature and telomere genes shared several common pathways, including cellular senescence (hsa04218) and proteoglycans in cancer (hsa05205). They also had overlapping GO-Molecular functions, such as DNA-binding transcription factor activity (GO:0003700), histone deacetylase binding (GO:0042826), and promoter-specific chromatin binding (GO:1990841). Conclusions: Our findings suggest an association between microRNAs and telomere genes, potentially playing significant roles in the survival of patients with ccRCC. The identified miRNA signature robustly predicts 5-year survival in ccRCC. The shared biological pathways between these miRNAs and telomere genes offer new insights into the mechanisms driving ccRCC, signaling potential for therapeutic targets and improved prognostic markers in kidney cancer. Citation Format: Srinivasulu Yerukala Sathipati, Rohit Sharma, Scott Hebbring. MicroRNA signature and telomere genes in kidney cancer survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4892.

Abstract 2993: TmiS: A prognostic indicator for prostate cancer survival based on total tumor cell miRNA levels

Abstract Background: MicroRNAs (miRNAs) are small noncoding RNAs that bind mRNA and inhibit translation or encourage degradation. MiRNAs play a significant regulatory role, with approximately 60% of protein-coding genes harboring miRNA binding sites. MiRNA dysregulation is associated with tumor onset, growth, and metastasis. These important regulatory RNAs have been studied as potential cancer biomarkers, yet the widespread adoption of any miRNA signature has been hindered by the variable nature of miRNA targeting, which is highly context specific. Total tumor cell mRNA content, or TmS, has been shown to have potential as a pan-cancer prognostic indicator. Here we expand the TmS framework using deconvolved miRNA expression to calculate TmiS, an estimate of total tumor-cell miRNA content and investigate the utility of TmiS as a prognostic marker in prostate cancer. Methods: Whole exome sequencing and miRNA sequencing, along with clinical annotations were downloaded for prostate cancer patient samples from The Cancer Genome Atlas (TCGA). Sample purity and ploidy were estimated from exomes using ASACT and ABSOLUTE. Tumor miRNA proportion was estimated using our previously developed miRNA deconvolution method DeMixMir, and TmiS, the total miRNA content per haploid genome per tumor cell, was calculated for each sample. Patients were separated by Gleason category and were binarized into High-TmiS and Low-TmiS within samples with Gleason 7 and Gleason 8+ scores separately. Results: We find Low-TmiS patients to have significantly better prognosis in both Gleason 7 (P = 0.04) and Gleason 8+ (P = 0.01) prostate cancer. We confirm that TmiS is indeed an aggregate measure of total miRNA levels, with no strong correlations observed with any one miRNA. We identify differentially expressed miRNAs and mRNAs between high and low TmiS, and find distinct enriched pathways between Gleason 7 and Gleason 8+ samples, and that several of the differentially expressed miRNAs are well-characterized cancer-related transcripts. Conclusions: In spite of their important regulatory function, the variable and context specific nature of miRNA targeting has been a barrier to their implementation as a robust biomarker. We find TmiS to be a measure of total miRNA dysregulation, and that patients with high total miRNA content show poorer survival within prostate samples graded at Gleason 7 (as well as Gleason 8+), which has been a challenging group for further risk classification. In summary, while the consequences of miRNA dysregulation are subtype specific, we find that by measuring total tumor cell miRNA, TmiS has potential as a robust prognostic indicator independent cellular context. Citation Format: Matthew Montierth, Kinga Németh, George A. Calin, Wenyi Wang. TmiS: A prognostic indicator for prostate cancer survival based on total tumor cell miRNA levels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2993.

RSPO2-associated mitochondrial metabolism defines molecular subtypes with distinct clinical and immune features in esophageal cancer.

Esophageal cancer is a highly aggressive malignancy with limited treatment options and poor prognosis. The identification of novel molecular subtypes and therapeutic targets is crucial for improving clinical outcomes. In this study, we investigated the role of R-spondin 2 (RSPO2) in esophageal cancer and its association with mitochondrial metabolism. Using bioinformatics analysis of publicly available datasets, we identified a panel of RSPO2-related mitochondrial metabolism genes and their expression patterns in esophageal cancer. Based on these genes, we stratified esophageal cancer patients into distinct molecular subtypes with different survival rates, immune cell infiltration profiles, and drug sensitivities. Our findings suggest that RSPO2-related mitochondrial metabolism genes may serve as potential therapeutic targets and prognostic markers for esophageal cancer. These genes play an important role in the prognosis, immune cell infiltration and drug sensitivity of esophageal cancer. The identified molecular subtypes provide valuable insights into the underlying molecular mechanisms of esophageal cancer and could guide personalized treatment strategies in the future.

Growth Hormone-Releasing Hormone as Potential Diagnostic and Therapeutic Target in Colorectal Cancer

Abstract: As the third most prevalent cancer, there is no convincing treatment for colorectal cancer. Growth Hormone-releasing Hormone (GHRH) is an important hormone for the growth and maturity of humans and other animals. Also, recent studies show both GHRH and GHRH receptor to be expressed in many types of cancers, such as lung, breast, colon, ovarian, gastric, and pancreatic cancer. GHRH has been shown to augment the growth and proliferation of cancer cells in in vivo and in vitro studies, but studies have shown that its antagonist can inhibit the growth or even metastasis of cancer cells. The development of many classes of GHRH-R antagonists over the past three decades has shown strong in vivo and in vitro growth inhibitory effects on cancer. The present study is an attempt to review the studies on the association between GHRH and colorectal cancer and examine if the hormone can be targeted for therapy or used as a prognostic marker for colorectal cancer or not.

CCNI2 promotes pancreatic cancer through PI3K/AKT signaling pathway.

Globally, pancreatic cancer is recognized as one of the deadliest malignancies that lacks effective targeted therapies. This study aims to explore the role of cyclin I-like protein (CCNI2), a homolog of cyclin I (CCNI), in the progression of pancreatic cancer, thereby providing a theoretical basis for its treatment. Firstly, the expression of CCNI2 in pancreatic cancer tissues was determined through immunohistochemical staining. The biological role of CCNI2 in pancreatic cancer cells was further assessed using both in vitro and in vivo loss/gain-of-function assays. Our data revealed that CCNI2 expression was abnormally elevated in pancreatic cancer, and clinically, increased CCNI2 expression generally correlated with reduced overall survival. Functionally, CCNI2 contributed to the malignant progression of pancreatic cancer by promoting the proliferation and migration of tumor cells. Consistently, in vivo experiments verified that CCNI2 knockdown impaired the tumorigenic ability of pancreatic cancer cells. Moreover, the addition of phosphatidylinositol 3-kinase (PI3K) inhibitors could partially reverse the promoting effect of CCNI2 on the malignant phenotypes of pancreatic cancer cells. CCNI2 promoted pancreatic cancer through PI3K/protein kinase B (AKT) signaling pathway, indicating its potential as a prognostic marker and therapeutic target for pancreatic cancer.

CeRNA Network and WGCNA Analyses of Differentially Expressed Genes in Cervical Cancer Tissues for Association with Survival of Patients.

The study aims to search and identify differentially expressed genes (DEGs) in cervical cancer tissues as novel biomarkers to predict cervical cancer prognosis. The Cancer Genome Atlas (TCGA) data on gene expression profiles in cervical cancer were downloaded and analyzed using R software to identify DEGs in cervical cancer tissues. miRNAs targeted by differentially expressed long non-coding RNAs (DElncRNAs) and mRNAs targeted by microRNAs (miRNAs) were identified using the online miRcode, miRTarBase, TargetScan, and miRDB tools. The ceRNA network and lncRNA expression modules in cervical cancer tissues were constructed using weighted gene co-expression network analysis (WGCNA) and analyzed bioinformatically. The Kaplan-Meier analysis was performed to confirm these DEGs as prognostic markers. Immunohistochemical (IHC) analysis was used to verify expression of the hub genes in 10 paired cervical cancer and normal tissues. A total of 1914 DEmRNAs, 210 DElncRNAs, and 67 DEmiRNAs were identified in cervical cancer samples. There were 39 lncRNAs, 19 miRNAs, and 87 mRNAs involved in the ceRNA network and 25 DElncRNAs, three DEmiRNAs, and four mRNAs involved in the ceRNA sub-network. CACNA1C-AS1 was associated with the yellow and blue modules in the ceRNA sub-network, and LIFR-AS1 was associated with the blue module. The DEmRNAs were involved in cancer-related pathways, and three hub genes (i.e., E2F1, CCNB1, and CCNE1) were highly expressed in cervical squamous cell carcinoma and adenocarcinoma tissues and associated with the prognosis of patients. The ceRNA network and WGCNA analyses are useful to identify novel DEGs that can serve as prognostic markers in cervical cancer. The DEGs will be validated in future studies.

RNA expression of 6 genes from metastatic mucosal gastric cancer serves as the global prognostic marker for gastric cancer with functional validation

BackgroundMolecular analysis of advanced tumors can increase tumor heterogeneity and selection bias. We developed a robust prognostic signature for gastric cancer by comparing RNA expression between very rare early gastric cancers invading only mucosal layer (mEGCs) with lymph node metastasis (Npos) and those without metastasis (Nneg).MethodsOut of 1003 mEGCs, all Npos were matched to Nneg using propensity scores. Machine learning approach comparing Npos and Nneg was used to develop prognostic signature. The function and robustness of prognostic signature was validated using cell lines and external datasets.ResultsExtensive machine learning with cross-validation identified the prognostic classifier consisting of four overexpressed genes (HDAC5, NPM1, DTX3, and PPP3R1) and two downregulated genes (MED12 and TP53), and enabled us to develop the risk score predicting poor prognosis. Cell lines engineered to high-risk score showed increased invasion, migration, and resistance to 5-FU and Oxaliplatin but maintained sensitivity to an HDAC inhibitor. Mouse models after tail vein injection of cell lines with high-risk score revealed increased metastasis. In three external cohorts, our risk score was identified as the independent prognostic factor for overall and recurrence-free survival.ConclusionThe risk score from the 6-gene classifier can successfully predict the prognosis of gastric cancer.

Crosstalk of cell death pathways unveils an autophagy-related gene AOC3 as a critical prognostic marker in colorectal cancer

The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC.

A Phase II Study of Rucaparib Monotherapy in Nonmetastatic, Hormone-Sensitive Prostate Cancer Demonstrating "BRCAness" Genotype (ROAR).

Both germline and somatic BReast CAncer gene (BRCA) mutations are poor prognostic markers in men with localized or metastatic prostate cancer. For instance, men with these mutations often are diagnosed with prostate cancer earlier and develop metastatic disease earlier compared with those who do not harbor similar mutations. Patients with germline alterations typically have more advanced disease and shorter overall survival (Castro E, Goh C, Olmos D, et al. Germline BRCA mutations are associated with higher risk of nodal involvement, distant metastasis, and poor survival outcomes in prostate cancer. J Clin Oncol. 2013;31(14):1748-1757. doi:10.1200/JCO.2012.43.1882). The risk of disease progression to metastatic disease is significant in patients with this genotype of prostate cancer. The percentage of patients free from metastatic disease was 90%, 72%, and 50%, respectively, compared with 97%, 94%, and 84% at 3, 5, and 10 years for patients with intact DNA repair (P < .001) (Castro E, Goh C, Leongamornlert D, et al. Effect of BRCA mutations on metastatic relapse and cause-specific survival after radical treatment for localised prostate cancer. Eur Urol. 2015;68(2):186-193. doi: 10.1016/j.eururo.2014.10.022). DNA damage repair non-BRCA mutations include alterations in genes such as ATM, CHEK2, PALB2, and RAD51. While less common than BRCA mutations, they have emerged as significant prognostic markers in prostate cancer. These BRCAness mutations are associated with a higher risk of aggressive disease and poorer survival outcomes. Given the debilitating physical and psychological side effects of androgen deprivation therapy (ADT) in relatively younger men with prostate cancer, delaying ADT in these men may be an attractive strategy. Given the proven efficacy of polyadenosine diphosphate-ribose polymerase (PARP) inhibitors in the castration-resistant prostate cancersetting, PARP inhibitor monotherapy in a nonmetastatic castration-sensitive (nmCSPC) setting has the potential to delay metastasis and delay the onset of ADT related symptoms. This is a single-arm, single-center, open-label, phase II trial to assess the efficacy of rucaparib in patients with high-risk biochemically recurrent (BCR) nmHSPC, which was defined as PSA doubling time of <9 months, demonstrating a "BRCAness" genotype (BRCA1/2 and other homologous recombination repair mutations). A total of 15 patients were intended to be enrolled, with an expected enrollment duration of 12 months. Patients were given rucaparib 600 mg orally twice daily and were allowed to remain on study treatment until PSA progression defined by Prostate Cancer Working Group 3, with 2 years of follow-up after study treatment. We anticipated a total of 2-3 years until completion of the clinical trial. The primary endpoint was to assess the PSA progression-free survival (PSA-PFS). The secondary endpoints of the study were safety, the proportion of patients with a PSA 50% response (PSA 50), and an undetectable PSA. A 4-week treatment duration comprised one cycle. The study started enrolling in June 2019 and was prematurely terminated in June 2022 after the accrual of 7 patients because of changing standard of care treatments with the introduction of next-generation scans, eg, prostate-specific membrane antigen positron emission tomography (PSMA-PET). Seven patients were enrolled in the study with the following pathogenic alterations: ATM (n = 3), BRCA2 (n = 2), BRCA1 (n = 1), BRIP1 (n = 1), and RAD51 (n = 1). The median duration of follow-up was 18 months. A median of 20 cycles (range 4-42) was completed, median PSA-PFS was 35.37 months (95% CI, 0-85.11 months). In total, 2 patients achieved PSA50; both also achieved nadir PSA as undetectable. Grade ≥ 3 adverse events (AEs) were anemia and rash (in 1 patient each). No dose-limiting toxicities or severe AEs were seen. Rucaparib demonstrated acceptable toxicity and efficacy signal as an ADT-sparing approach in patients with biochemically recurrent nonmetastatic prostate cancer. It is currently challenging to understand the optimal value of systemic therapy in this disease setting due to the rapidly changing standard of care. Additionally, there are relatively few patients with BRCAness who present with nonmetastatic hormone-sensitive prostate cancer (ClinicalTrials.gov Identifier: NCT03533946).