LRP1B deletion in high-grade serous ovarian cancers is associated with acquired chemotherapy resistance to liposomal doxorubicin

Targeting ovarian cancer: The promise of liposome-based therapies

A major cause of mortality among gynecological cancers, ovarian cancer is frequently unresponsive to standard therapies because to systemic toxicity and medication resistance. The contribution of liposomal drug delivery systems, specifically pegylated liposomal doxorubicin (PLD), to the advancement of ovarian cancer treatment is examined in this review. Liposomes, spherical lipid vesicles consisting of bilayer phospholipids, enable better drug delivery by preserving encapsulated pharmaceuticals and enabling tailored administration to tumor areas. In comparison to traditional doxorubicin, PLD has a better pharmacokinetic profile and less cardiotoxicity, according to the analysis, which examines several trials showing its effectiveness in treating both platinum-sensitive and platinum-resistant ovarian cancer. Furthermore, studies on liposomal versions of other medications, such as paclitaxel and cisplatin, demonstrate encouraging effects in terms of overcoming drug resistance and enhancing therapeutic outcomes. Recent advancements in tailored liposomal delivery systems that include components such tumor-specific peptides and folate receptors show improved tumor selectivity and fewer adverse effects. The study also looks at new combination treatments that use liposomal formulations with immunotherapeutic and new targeted medicines. Although liposomal drug delivery methods have great potential for treating ovarian cancer, further study is required to maximize their effectiveness, reduce side effects, and get beyond resistance mechanisms. These developments in liposomal technology are a major step toward turning ovarian cancer from a deadly illness into a chronic condition that can be managed, possibly increasing patient survival and quality of life.

High-throughput microfluidic spheroid technology for early detection of colistin-induced nephrotoxicity with gradient-based analysis

Colistin is essential for treating multidrug-resistant Gram-negative bacterial infections but has significant nephrotoxic side effects. Traditional approaches for studying colistin's nephrotoxicity are challenged by the rapid metabolism of its prodrug, colistin methanesulfonate and the difficulty of obtaining adequate plasma from critically ill patients. To address these challenges, we developed the Spheroid Nephrotoxicity Assessing Platform (SNAP), a microfluidic device that efficiently detects colistin-induced toxicity in renal proximal tubular epithelial cell (RPTEC) spheroids within 48 hours using just 200 μL of patient plasma. Our findings demonstrate that SNAP not only promotes higher expression of kidney-specific markers aquaporin-1 (AQP1) and low-density lipoprotein receptor-related protein 2 (LRP2) compared to traditional two-dimensional (2D) cultures, but also exhibits increased sensitivity to colistin, with significant toxicity detected at concentrations of 50 μg ml-1 and above. Notably, SNAP's non-invasive method did not identify nephrotoxicity in plasma from healthy donors, thereby confirming its physiological relevance and showcasing superior sensitivity over 2D cultures, which yielded false-positive results. In clinical validation, SNAP accurately identified patients at risk of colistin-induced nephrotoxicity with 100% accuracy for both early and late onset and demonstrated a 75% accuracy rate in predicting the non-occurrence of nephrotoxicity. These results underline the potential of SNAP in personalized medicine, offering a non-invasive, precise and efficient tool for the assessment of antibiotic-induced nephrotoxicity, thus enhancing the safety and efficacy of treatments against resistant bacterial infections.

LRP1B Suppresses Immunotherapy Efficacy in Lung Adenocarcinoma by Preventing Ferroptosis

BACKGROUND

Immune biomarkers for non-small-cell lung cancer (NSCLC) are programmed death ligand 1 (PD-L1) and tumor mutational burden (TMB). However, they cannot accurately predict the effectiveness of immunotherapy. Identifying appropriate biomarkers that can differentiate between beneficiary groups is imperative.

METHODS

We identified lipoprotein receptor-related protein 1B (LRP1B) mutation as a potential biomarker for immunotherapy by analyzing clinical data, combined with bioinformatics analysis. The effects of LRP1B on ferroptosis were assessed using qRT-PCR, Western blotting, CCK-8 assay, and flow cytometry. The potential mechanism underlying the regulation of ferroptosis by LRP1B was elucidated using qRT-PCR, Western blotting, ChIP, and dual-luciferase reporter gene assays.

RESULTS

Through the collection and analysis of clinical data, we had established that LRP1B mutations are closely associated with immunotherapy. Bioinformatics analysis revealed significant differences in the expression levels of PD-L1 and TMB between patients with LRP1B mutation and wild-type patients in lung adenocarcinoma (LUAD). Furthermore, we observed that patients with LRP1B mutation in LUAD had significantly higher levels of tumor-infiltrating lymphocytes (TILs) than wild-type patients. In addition, we found that patients with LRP1B mutation in LUAD had significantly prolonged progression-free survival (PFS) compared to wild-type patients. However, the differences of PD-L1 expression, TILs, and PFS were not observed in patients with LRP1B mutation in lung squamous cell carcinoma (LUSC). These findings provided strong evidence that LRP1B mutation was a potential biomarker for immunotherapy in LUAD. Moreover, our in vivo experiments indicated that knockdown of LRP1B enhanced the efficacy of mPD-1, and mechanistic studies revealed that LRP1B regulated the sensitivity of cells to ferroptosis by modulating the expression of SLC7A11 through altering the phosphorylation level of STAT3. Further analysis revealed that LRP1B knockdown promoted immunotherapy in vivo.

CONCLUSIONS

Our results confirmed that LRP1B affected the efficacy of immunotherapy by modulating the sensitivity of NSCLC cells to ferroptosis. LRP1B mutations represent a highly promising immunotherapeutic biomarker for NSCLC.

Pathogenic loss-of-function mutations in LRP1B are associated with poor survival in head and neck cancer patients

OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) present a significant challenge in the medical field due to treatment resistance, which often hinders successful outcomes. The dysregulation of the LRP1B gene is linked to various cancers, but its specific role in HNSCC is poorly understood.

METHODS

This study investigated the link between pathogenic loss-of-function mutations in the LRP1B gene and survival outcomes in HNSCC patients. The Cancer Genome Atlas HNSCC cohort, comprised of 520 tumor and 44 normal tissues, was analyzed using cBioportal, and UALCAN tools. Expression patterns, survival outcomes, and clinical correlations of LRP1B were evaluated. In-depth analyses involved validation of mRNA expression using RT-qPCR and functional exploration using various in-silico tools.

RESULTS

Analysis of data from The Cancer Genome Atlas (TCGA) and cBioPortal revealed a high frequency (25 %) of LRP1B mutations in HNSCC patients. Notably, splice mutation, truncating mutation, and deep deletion, considered potential drivers, are commonly associated with LRP1B mutations. Patients with LRP1B mutations also exhibit poorer overall survival rates compared to those without these mutations. Furthermore, LRP1B mRNA expression is significantly reduced in HNSCC tissues compared to normal tissues and is correlated with advanced tumor stage, higher tumor grade, and nodal metastasis.

CONCLUSION

These findings indicate that LRP1B may function as both a prognostic biomarker and a therapeutic target in HNSCC patients.

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes

BACKGROUND

Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging.

METHODS

To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes.

RESULTS

We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities.

CONCLUSIONS

Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.

Discovery of Novel Potential Prognostic Markers and Targeted Therapy to Overcome Chemotherapy Resistance in an Advanced-Stage Wilms Tumor

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced-stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced-stage WTs, of which 7 cases were chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in advanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemotherapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profiles of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

Full-spectral genome analysis of natural killer/T cell lymphoma highlights impacts of genome instability in driving its progression

BACKGROUND

Natural killer/T cell lymphoma (NKTCL) is a clinically and genetically heterogeneous disease with poor prognosis. Genome sequencing and mutation characterization provides a powerful approach for patient stratification, treatment target discovery, and etiology identification. However, previous studies mostly concentrated on base-level mutations in primary NKTCL, whereas the large-scale genomic alterations in NKTCL and the mutational landscapes in relapsed/refractory NKTCL remain largely unexplored.

METHODS

Here, we assembled whole-genome sequencing and whole-exome sequencing data from 163 patients with primary or relapsed/refractory NKTCL and compared their somatic mutational landscapes at both nucleotide and structure levels.

RESULTS

Our study not only confirmed previously reported common NKTCL mutational targets like STAT3, TP53, and DDX3X but also unveiled several novel high-frequency mutational targets such as PRDM9, DST, and RBMX. In terms of the overall mutational landscape, we observed striking differences between primary and relapsed/refractory NKTCL patient groups, with the latter exhibits higher levels of tumor mutation burden, copy number variants (CNVs), and structural variants (SVs), indicating a strong signal of genomic instability. Complex structural rearrangements such as chromothripsis and focal amplification are also significantly enriched in relapsed/refractory NKTCL patients, exerting a substantial impact on prognosis. Accordingly, we devised a novel molecular subtyping system (i.e., C0-C4) with distinct prognosis by integrating potential driver mutations at both nucleotide and structural levels, which further provides an informative guidance for novel treatments that target these specific driver mutations and genome instability as a whole.

CONCLUSIONS

The striking differences underlying the mutational landscapes between the primary and relapsed/refractory NKTCL patients highlight the importance of genomic instability in driving the progression of NKTCL. Our newly proposed molecular subtyping system is valuable in assisting patient stratification and novel treatment design towards a better prognosis in the age of precision medicine.

Pan-Cancer Single-Nucleus Total RNA Sequencing Using snHH-Seq

Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single-cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA-seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high-throughput and high-sensitivity method called snHH-seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full-length RNA-seq data is also established. snHH-seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan-cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full-length RNA at the single-nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology.

Mapping the landscape of HPV integration and characterising virus and host genome interactions in HPV-positive oropharyngeal squamous cell carcinoma

BACKGROUND

Human papillomavirus (HPV) integration into the host genome is an important factor in HPV(+)OPSCC carcinogenesis, in conjunction with HPV oncoproteins E6/E7. However, a well-studied investigation about virus-host interaction still needs to be completed. Our objective is to characterise HPV integration to investigate potential mechanisms of tumourigenesis independent of E6/E7 oncoproteins.

MATERIALS AND METHODS

High-throughput viral integration detection was performed on 109 HPV(+)OPSCC tumours with relevant clinicopathological information. Of these tumours, 38 tumours underwent targeted gene sequencing, 29 underwent whole exome sequencing and 26 underwent RNA sequencing.

RESULTS

HPV integration was detected in 94% of tumours (with a mean integration count of 337). Tumours occurring at the tonsil/oropharyngeal wall that exhibit higher PD-L1 expression demonstrated increased integration sites (p = .024). HPV exhibited a propensity for integration at genomic sites located within specific fragile sites (FRA19A) or genes associated with functional roles such as cell proliferation and differentiation (PTEN, AR), immune evasion (CD274) and glycoprotein biosynthesis process (FUT8). The viral oncogenes E2, E4, E6 and E7 tended to remain intact. HPV fragments displayed enrichment within host copy number variation (CNV) regions. However, insertions into genes related to altered homologous recombination repair were infrequent. Genes with integration had distinct expression levels. Fifty-nine genes whose expression level was affected by viral integration were identified, for example, EPHB1, which was reported to be involved in cellular protein metabolic process.

CONCLUSIONS

HPV can promote oncogenesis through recurrent integration into functional host genome regions, leading to subsequent genomic aberrations and gene expression disruption. This study characterises viral integrations and virus-host interactions, enhancing our understanding of HPV-related carcinogenesis mechanisms.

LRP1B-a prognostic marker in tubo-ovarian high-grade serous carcinoma

Low-density lipoprotein (LDL) receptor-related protein 1B (LRP1B) is a member of the LDL receptor family and has often been discussed as a tumor suppressor gene, as its down-regulation is correlated with a poor prognosis in multiple carcinoma entities. Due to the high metastasis rate into the fatty peritoneal cavity and current research findings showing a dysregulation of lipid metabolism in tubo-ovarian high-grade serous carcinoma (HGSC), we questioned the prognostic impact of the LRP1B protein expression. We examined a well-characterized large cohort of 571 patients with primary HGSC and analyzed the LRP1B protein expression via immunohistochemical staining (both in tumor and stroma cells separately), performed precise bioimage analysis with QuPath, and calculated the prognostic impact using SPSS. Our results demonstrate that LRP1B functions as a significant prognostic marker for overall survival (OS) and progression-free survival (PFS) in HGSC on the protein level. High cytoplasmic expression of LRP1B in tumor, stroma, and combined tumor and stroma cells has a significantly positive association with a mean prolongation of the OS by 42 months (P = .005), 29 months (P = .005), and 25 months (P = .001), respectively. Additionally, the mean PFS was 18 months longer in tumor (P = .002), 19 months in stroma (P = .004), and 19 months in both cell types combined (P = .01). Our results remained significant in multivariate analysis. We envision LRP1B as a potential prognostic tool that could help us understand the functional role of lipid metabolism in advanced HGSC, especially regarding liposomal medications.

Loss of LRP1B expression drives acquired chemo and radio-resistance in HPV-positive head and neck cancer

OBJECTIVES

Although human papillomavirus positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) patients typically experience excellent survival, 15-20 % of patients recur after treatment with chemotherapy and radiation. Therefore, there is a need for biomarkers of treatment failure to guide treatment intensity.

MATERIALS AND METHODS

Whole genome sequencing was carried out on HPV+OPSCC patients who were primarily treated with concurrent chemotherapy (cisplatin) and radiation. We then explored whether the loss of LRP1Bwas sufficient to drive an aggressive phenotype, and promote a resistance to cisplatin and radiation therapy both in vitro using HPV+ cell lines (93VU147T, UMSCC47, UWO37 and UWO23) and in vivo.

RESULTS

Through integrative genomic analysis of three HPV+OPSCC tumour datasets, we identified that deletion of LRP1B was enriched in samples that recurred following chemo-radiation. Knockdown using siRNA in four HPV+ cell lines (UWO23, UWO37, UMSCC47 and 93VU147T) resulted in increased proliferation of all cases. CRISPR/Cas9 deletion of LRP1B in the same cell line panel demonstrated increased proliferation, clonogenic growth and migration, as well as resistance to both cisplatin and radiation in LRP1B deleted cells compared to their respective non-targeting control cells. Cell line derived xenograft studies indicated that the LRP1B knockout tumours were more resistant to cisplatin and radiation therapy compared to their controls invivo.

CONCLUSION

Taken together, our work implicates LRP1B deletion as a potential biomarker for identifying treatment resistant HPV+ OPSCC cases.

Mutant-allele dispersion correlates with prognosis risk in patients with advanced non-small cell lung cancer

BACKGROUND

Intra-tumor heterogeneity (ITH) contributes to lung cancer progression and resistance to therapy. To evaluate ITH and determine whether it may be employed as a predictive biomarker of prognosis in patients with advanced non-small cell lung cancer (NSCLC), we used a novel algorithm called mutant-allele dispersion (MAD).

METHODS

In the study, 103 patients with advanced NSCLC were enrolled. Using a panel of 425 cancer-related genes, next-generation sequencing (NGS) was performed on tumor specimens that had been collected. From NGS data, we derived MAD values, and we next looked into their relationships with clinical variables and different mutation subtypes.

RESULTS

The median MAD among 103 NSCLC patients was 0.73. EGFR mutation, tyrosine kinase inhibitor (TKI) therapy, radiotherapy, and chemotherapy cycles were all substantially correlated with the MAD score. In patients with lung adenocarcinoma (LUAD), correlation analysis revealed that the MAD score was substantially linked with Notch pathway mutation (P = 0.021). A significant relationship between high MAD and shorter progression-free survival (PFS) was found (HR = 2.004, 95%CI 1.269-3.163, P = 0.003). In patients with advanced NSCLC, histological type (P = 0.004), SMARCA4 mutation (P = 0.038), and LRP1B mutation (P = 0.006) were all independently associated with prognosis. The disease control rate was considerably greater in the low MAD group compared to the high MAD group in 19 LUAD patients receiving immunotherapy (92.9% vs. 40%, P = 0.037). TKI-PFS was longer in 37 patients with low MAD who received first-line TKI therapy (P = 0.014).

CONCLUSION

Our findings suggested that MAD is a practical and simple algorithm for assessing ITH, and populations with high MAD values are more likely to have EGFR mutations. MAD can be used as a potential biomarker to predict not only the prognosis of NSCLC but also the efficacy of immunotherapy and TKI therapy in patients with advanced NSCLC.

Using a Dual CRISPR/Cas9 Approach to Gain Insight into the Role of LRP1B in Glioblastoma

LRP1B remains one of the most altered genes in cancer, although its relevance in cancer biology is still unclear. Recent advances in gene editing techniques, particularly CRISPR/Cas9 systems, offer new opportunities to evaluate the function of large genes, such as LRP1B. Using a dual sgRNA CRISPR/Cas9 gene editing approach, this study aimed to assess the impact of disrupting LRP1B in glioblastoma cell biology. Four sgRNAs were designed for the dual targeting of two LRP1B exons (1 and 85). The U87 glioblastoma (GB) cell line was transfected with CRISPR/Cas9 PX459 vectors. To assess LRP1B-gene-induced alterations and expression, PCR, Sanger DNA sequencing, and qRT-PCR were carried out. Three clones (clones B9, E6, and H7) were further evaluated. All clones presented altered cellular morphology, increased cellular and nuclear size, and changes in ploidy. Two clones (E6 and H7) showed a significant decrease in cell growth, both in vitro and in the in vivo CAM assay. Proteomic analysis of the clones' secretome identified differentially expressed proteins that had not been previously associated with LRP1B alterations. This study demonstrates that the dual sgRNA CRISPR/Cas9 strategy can effectively edit LRP1B in GB cells, providing new insights into the impact of LRP1B deletions in GBM biology.

Survey of genomic and physiological characteristics for survival in lymphoma: The NCI genomic data portal

Lymphoma represents a myriad collection of neoplasms that impact lymphocytes. This cancer often involves disrupted cytokine, immune surveillance, and gene regulatory signaling, sometimes with expression of Epstein Barr Virus (EBV). We explored mutation patterns for People experiencing Lymphoma (PeL) in the National Cancer Institute (NCI) Genomic Data Commons (GDC), which contains detailed, deidentified genomic data on 86,046 people who have/had cancer with 2,730,388 distinctive mutations in 21,773 genes. The database included information on 536 (PeL), with the primary focal sample being the n = 30 who had complete mutational genomic data. We used correlations, independent samples t-tests, and linear regression to compare PeL demographics and vital status on mutation numbers, BMI, and mutation deleterious score across functional categories of 23 genes. PeL demonstrated varied patterns of mutated genes, consistent with most other cancer types. The primary PeL gene mutations clustered around five functional protein groups: transcriptional regulatory proteins, TNF/NFKB and cell signaling regulators, cytokine signaling proteins, cell cycle regulators, and immunoglobulins. Diagnosis Age, Birth Year, and BMI negatively (P < 0.05) correlated with Days to Death, and cell cycle mutations negatively correlated (P = 0.004) with survival days (R² = 0.389). There were commonalities in some PeL for mutations across other cancer types based upon large sequence length, but also for 6 small cell lung cancer genes. Immunoglobulin mutations were prevalent but not for all cases. Research indicates a need for greater personalized genomics and multi-level systems analysis to evaluate facilitators and barriers for lymphoma survival.

Alteration in glycolytic/cholesterogenic gene expression is associated with bladder cancer prognosis and immune cell infiltration

Background

Oncogenic metabolic reprogramming contributes to tumor growth and immune evasion. The intertumoral metabolic heterogeneity and interaction of distinct metabolic pathways may determine patient outcomes. In this study, we aim to determine the clinical and immunological significance of metabolic subtypes according to the expression levels of genes related to glycolysis and cholesterol-synthesis in bladder cancer (BCa).

Methods

Based on the median expression levels of glycolytic and cholesterogenic genes, patients were stratified into 4 subtypes (mixed, cholesterogenic, glycolytic, and quiescent) in an integrated cohort including TCGA, GSE13507, and IMvigor210. Clinical, genomic, transcriptomic, and tumor microenvironment characteristics were compared between the 4 subtypes.

Results

The 4 metabolic subtypes exhibited distinct clinical, molecular, and genomic patterns. Compared to quiescent subtype, mixed subtype was more likely to be basal tumors and was significantly associated with poorer prognosis even after controlling for age, gender, histological grade, clinical stage, and molecular phenotypes. Additionally, mixed tumors harbored a higher frequency of RB1 and LRP1B copy number deletion compared to quiescent tumors (25.7% vs. 12.7 and 27.9% vs. 10.2%, respectively, both adjusted P value< 0.05). Furthermore, aberrant PIK3CA expression level was significantly correlated with those of glycolytic and cholesterogenic genes. The quiescent subtype was associated with lower stemness indices and lower signature scores for gene sets involved in genomic instability, including DNA replication, DNA damage repair, mismatch repair, and homologous recombination genes. Moreover, quiescent tumors exhibited lower expression levels of pyruvate dehydrogenase kinases 1-3 (PDK1-3) than the other subtypes. In addition, distinct immune cell infiltration patterns were observed across the 4 metabolic subtypes, with greater infiltration of M0/M2 macrophages observed in glycolytic and mixed subtypes. However, no significant difference in immunotherapy response was observed across the 4 metabolic subtypes.

Conclusion

This study proposed a new metabolic subtyping method for BCa based on genes involved in glycolysis and cholesterol synthesis pathways. Our findings may provide novel insight for the development of personalized subtype-specific treatment strategies targeting metabolic vulnerabilities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09064-0.

Mechanistic Insights Delineating the Role of Cholesterol in Epithelial Mesenchymal Transition and Drug Resistance in Cancer

Despite the significant advancements made in targeted anti-cancer therapy, drug resistance constitutes a multifaceted phenomenon leading to therapy failure and ultimately mortality. Emerging experimental evidence highlight a role of cholesterol metabolism in facilitating drug resistance in cancer. This review aims to describe the role of cholesterol in facilitating multi-drug resistance in cancer. We focus on specific signaling pathways that contribute to drug resistance and the link between these pathways and cholesterol. Additionally, we briefly discuss the molecular mechanisms related to the epithelial-mesenchymal transition (EMT), and the documented link between EMT, metastasis and drug resistance. We illustrate this by specifically focusing on hypoxia and the role it plays in influencing cellular cholesterol content following EMT induction. Finally, we provide a proposed model delineating the crucial role of cholesterol in EMT and discuss whether targeting cholesterol could serve as a novel means of combatting drug resistance in cancer progression and metastasis.

Epiphycan Predicts Poor Outcomes and Promotes Metastasis in Ovarian Cancer

The small leucine-rich proteoglycan (SLRP) family is widely expressed in extracellular matrix and aggravates tumor progression. However, epiphycan (EPYC), as a member of the SLRPs family, its biological function in cancer has not been confirmed. Thus, we aimed to clarify the role of EPYC in progression of ovarian cancer (OC), and further analyze the molecular mechanisms implicated in tumorigenesis. Here, we analyzed the differential expression genes of GSE38734, including 4 matched primary OC and metastatic tissues. We obtained OC RNAseqs data from the Cancer Genome Atlas (TCGA) and analyzed the correlation between EPYC expression and OC staging, pathological grading, etc. The expression of EPYC in OC and normal ovarian tissues was compared in Oncomine website. We used siRNAs to interfere the expression of EPYC in ovarian cancer cell line SKOV3. Scratch test, transwell-matrigel chamber, CCK8 assay were used to detect the changes of SKOV3 migration, invasion and proliferation ability after EPYC was interfered. We used R software to make GO and KEGG analysis of related genes of EPYC. We used the Hitpredict website to predict interacting proteins. The results showed that the expression of EPYC in metastatic ovarian cancer was higher than primary ovarian cancer, and that in primary cancer was higher than normal ovaries. After siRNA interferes with EPYC expression, the migration, invasion and proliferation of SKOV3 cells were weakened. EPYC mainly played a role in ECM organization, and involved in PI3K/Akt, focal adhesion signaling pathways. EPYC might interact with PLCG2 and CRK, and be involved in signal transduction.

LRP1B Expression as a Putative Predictor of Response to Pegylated Liposomal Doxorubicin Treatment in Ovarian Cancer

BACKGROUND

Pegylated liposomal doxorubicin (PLD) is among the most active therapies for recurrent/progressive ovarian cancer (OC). Low-density lipoprotein receptor-related protein 1B (LRP1B) is one of the 10 most significantly deleted genes in human cancers. It mediates endocytosis of several factors from the cellular environment including liposomes. Although the LRP1B role in cancer has not been fully disclosed, its contribution to resistance to liposomal therapies has been hypothesized. This study aimed to evaluate the impact of LRP1B protein as a possible marker of response to PLD in patients with OC.

METHODS

LRP1B expression and response to PLD were analyzed in OC cell lines by qRT-PCR and PrestoBlue viability assay, respectively. LRP1B protein expression was evaluated for the first time, in tumor samples from PLD-treated patients and controls (other chemotherapies) by immunohistochemistry. Association of LRP1B staining score (determined based on intensity and percentage of positively stained cells) with clinicopathological features, response to therapy and survival outcomes was evaluated.

RESULTS

OC cells with increased expression of LRP1B were more sensitive to PLD. LRP1B staining score was associated with clinicopathological features, response to therapy, and survival outcomes. Higher LRP1B levels were associated with prolonged progression-free survival. This association was more evident in patients treated with PLD and in responders to PLD.

CONCLUSION

Our results support a possible role of LRP1B as a predictor of response to PLD in patients with OC.

Integrating Cancer Vaccines in the Standard-of-Care of Ovarian Cancer: Translating Preclinical Models to Human

Simple Summary

The overall survival of ovarian cancer (OC) remains poor for most patients. Despite incorporation of novel therapeutic agents such as bevacizumab and PARP inhibitors to OC standard-of-care, efficacy is only observed in a subset of patients. Cancer vaccination has demonstrated effectiveness in OC patients and could be considered for potential incorporation into OC standard-of-care. This review provides an overview of the different types of cancer vaccination strategies and discusses the use of murine OC tumor models to evaluate combinatorial regimens comprising cancer vaccines and OC standard-of-care.

Abstract

As the majority of ovarian cancer (OC) patients are diagnosed with metastatic disease, less than 40% will survive past 5 years after diagnosis. OC is characterized by a succession of remissions and recurrences. The most promising time point for immunotherapeutic interventions in OC is following debulking surgery. Accumulating evidence shows that T cells are important in OC; thus, cancer vaccines capable of eliciting antitumor T cells will be effective in OC treatment. In this review, we discuss different cancer vaccines and propose strategies for their incorporation into the OC standard-of-care regimens. Using the murine ID8 ovarian tumor model, we provide evidence that a cancer vaccine can be effectively combined with OC standard-of-care to achieve greater overall efficacy. We demonstrate several important similarities between the ID8 model and OC patients, in terms of response to immunotherapies, and the ID8 model can be an important tool for evaluating combinatorial regimens and clinical trial designs in OC. Other emerging models, including patient-derived xenograft and genetically engineered mouse models, are continuing to improve and can be useful for evaluating cancer vaccination therapies in the near future. Here, we provide a comprehensive review of the completed and current clinical trials evaluating cancer vaccines in OC.

LRP1B: A Giant Lost in Cancer Translation

Low-density lipoprotein receptor-related protein 1B (LRP1B) is a giant member of the LDLR protein family, which includes several structurally homologous cell surface receptors with a wide range of biological functions from cargo transport to cell signaling. LRP1B is among the most altered genes in human cancer overall. Found frequently inactivated by several genetic and epigenetic mechanisms, it has mostly been regarded as a putative tumor suppressor. Still, limitations in LRP1B studies exist, in particular associated with its huge size. Therefore, LRP1B expression and function in cancer remains to be fully unveiled. This review addresses the current understanding of LRP1B and the studies that shed a light on the LRP1B structure and ligands. It goes further in presenting increasing knowledge brought by technical and methodological advances that allow to better manipulate LRP1B expression in cells and to more thoroughly explore its expression and mutation status. New evidence is pushing towards the increased relevance of LRP1B in cancer as a potential target or translational prognosis and response to therapy biomarker.

Chromoanagenesis Landscape in 10,000 TCGA Patients

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor's nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

Gene network analysis to determine the effect of hypoxia-associated genes on brain damages and tumorigenesis using an avian model

BACKGROUND

Hypoxia refers to the condition of low oxygen pressure in the atmosphere and characterization of response to hypoxia as a biological complex puzzle, is challenging. Previously, we carried out a comparative genomic study by whole genome resequencing of highland and lowland Iranian native chickens to identify genomic variants associated with hypoxia conditions. Based on our previous findings, we used chicken as a model and the identified hypoxia-associated genes were converted to human's orthologs genes to construct the informative gene network. The main goal of this study was to visualize the features of diseases due to hypoxia-associated genes by gene network analysis.

RESULTS

It was found that hypoxia-associated genes contained several gene networks of disorders such as Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and cancers. We found that biological pathways are involved in mitochondrion dysfunctions including peroxynitrous acid production denoted in brain injuries. Lewy body and neuromelanin were reported as key symptoms in Parkinson disease. Furthermore, calmodulin, and amyloid precursor protein were detected as leader proteins in Alzheimer's diseases. Dexamethasone was reported as the candidate toxic drug under the hypoxia condition that implicates diabetes, osteoporosis, and neurotoxicity. Our results suggested DNA damages caused by the high doses of UV radiation in high-altitude conditions, were associated with breast cancer, ovarian cancer, and colorectal cancer.

CONCLUSIONS

Our results showed that hypoxia-associated genes were enriched in several gene networks of disorders including Parkinson, Alzheimer, cardiomyopathy, drug toxicity, and different types of cancers. Furthermore, we suggested, UV radiation and low oxygen conditions in high-altitude regions may be responsible for the variety of human diseases.

Controversies in the Management of Early-stage Serous Endometrial Cancer

BACKGROUND/AIM

Early-stage uterine serous carcinoma (USC) has one of the highest recurrence rates and mortality among early-stage uterine epithelial cancers. Research into the clinical management of USC has begun to progress, guided by surgical and pathological advances. This article summarizes the available literature regarding diagnosis, management, and possible future uses of molecular analysis of women with early-stage USC.

MATERIALS AND METHODS

PubMed was searched for all pertinent English language research articles published from January 1, 2006 through March 1, 2020 which included a study population of women diagnosed with stage 1 USC. Due to the scarcity of prospective or large-scale data, studies were not limited by design or numbers of patients. Studies performed at earlier dates were incorporated to provide context.

RESULTS

A total of 86 studies were included in the review. Multiple well-designed studies have confirmed the safety of a minimally invasive surgical approach for surgical management of USC. The role of sentinel node biopsy has been validated with both prospective and retrospective multi-center data. Stage I USC is associated with a highly variable risk of recurrence, even following completion of adjuvant chemoradiation. This aggressive phenotype has been linked to high numbers of somatic copy number alterations, tumor protein 53, and phosphatidylinositol 3 kinase mutations, which have been shown to be predictive of prognosis.

CONCLUSION

Early-stage USC demonstrates a lack of predictable recurrence patterns, with reports noting distant recurrence in patients with disease confined to polyps. Unless no residual tumor is found on hysterectomy, chemotherapy and radiotherapy should be discussed and individualized by stage and treatment goals.

Molecular characterization of endometrial cancer and therapeutic implications

PURPOSE OF REVIEW

The present article reviews molecular subtyping and genomic characterization of endometrial carcinoma, and the associated therapeutic and prognostic implications.

RECENT FINDINGS

Endometrial cancer has historically been classified through histology into endometrioid and nonendometrioid subtypes with poor prognostic predictability. Molecular classification through genomic analysis now allows for a major advance in characterization. Four distinct subgroups have been identified: polymerase (POLE) ultramutated, microsatellite unstable, copy number-low--microsatellite stable, and copy number-high-'serous-like'. These subtypes have prognostic implications and may aid in the identification of early-stage patients who are at high risk for recurrence. Through analysis of surrogate markers (POLE, MSI, and p53) and other validated molecular alterations (L1CAM), it is possible to obtain an integrated molecular risk profile that relates to prognosis. Studies utilizing this risk profile in order to identify patients who may benefit from adjuvant treatment for early-stage disease are on-going.

SUMMARY

Molecular characterization of endometrial cancer into subgroups has enhanced prognostic and therapeutic implications, contrary to traditional risk stratification. Further development of an integrated molecular risk profile may identify patients who could most benefit from adjuvant treatment following surgery and tailor treatment decisions in the recurrent setting.

Uterine serous carcinoma

Serous endometrial cancer represents a relative rare entity accounting for about 10% of all diagnosed endometrial cancer, but it is responsible for 40% of endometrial cancer-related deaths. Patients with serous endometrial cancer are often diagnosed at earlier disease stage, but remain at higher risk of recurrence and poorer prognosis when compared stage-for-stage with endometrioid subtype endometrial cancer. Serous endometrial cancers are characterized by marked nuclear atypia and abnormal p53 staining in immunohistochemistry. The mainstay of treatment for newly diagnosed serous endometrial cancer includes a multi-modal therapy with surgery, chemotherapy and/or radiotherapy. Unfortunately, despite these efforts, survival outcomes still remain poor. Recently, The Cancer Genome Atlas (TCGA) Research Network classified all endometrial cancer types into four categories, of which, serous endometrial cancer mostly is found within the "copy number high" group. This group is characterized by the increased cell cycle deregulation (e.g., CCNE1, MYC, PPP2R1A, PIKCA, ERBB2 and CDKN2A) and TP53 mutations (90%). To date, the combination of pembrolizumab and lenvatinib is an effective treatment modality in second-line therapy, with a response rate of 50% in advanced/recurrent serous endometrial cancer. Owing to the unfavorable outcomes of serous endometrial cancer, clinical trials are a priority. At present, ongoing studies are testing novel combinations of various targeted and immunotherapeutic agents in newly diagnosed and advanced/recurrent endometrial cancer - an important strategy for serous endometrial cancer, whereby tumors are usually p53+ and pMMR, making response to PD-1 inhibitor monotherapy unlikely. Here, the rare tumor working group (including members from the European Society of Gynecologic Oncology (ESGO), Gynecologic Cancer Intergroup (GCIG), and Japanese Gynecologic Oncology Group (JGOG)), performed a narrative review reporting on the current landscape of serous endometrial cancer and focusing on standard and emerging therapeutic options for patients affected by this difficult disease.

LRP1B mutation is associated with tumor HPV status and promotes poor disease outcomes with a higher mutation count in HPV-related cervical carcinoma and head & neck squamous cell carcinoma

Human papillomavirus (HPV) infection and gene mutations were reputed as key factors in cervical carcinoma (CC) and head and neck squamous cell carcinoma (HNSCC). However, the associations of HPV status and gene mutations remain to be determined. This study aims to identify molecular patterns of LRP1B mutation and HPV status via rewiring tumor samples of HNSCC (n=1478) and CC (n=178) from the TCGA dataset. Here, we found that LRP1B mutation was associated with HPV status in CC (P=0.040) and HNSCC (P=0.044), especially in HPV 16 integrated CC (P=0.036). Cancer survival analysis demonstrated that samples with LRP1B mutation showed poor disease outcomes in CC (P=0.013) and HNSCC (P=0.0124). In addition, the expression status of LPR1B was more favorable for prediction than TP53 or RB1 in CC and HNSCC. Mutation clustering analysis showed that samples with LRP1B mutation showed higher mutation count in CC (P=1.76e-67) and HNSCC (P<10e-10). Further analysis identified 289 co-occurrence genes in these two cancer types, which were enriched in PI3K signaling, cell division process, and chromosome segregation process, et al. The 289-co-occurrence gene signature identified a cluster of patients with a higher portion of copy number variation (CNV) lost in the genome, different tumor HPV status (P<10e-10), higher mutation count (P<10e-10), higher fraction genome altered value (P=2.078e-4), higher aneuploidy score (P=3.362e-4), and earlier started the smoking year (P=2.572e-4), which were associated with shorter overall survival (P=0.0103) in CC and HNSCC samples. Overall, LRP1B mutation was associated with tumor HPV status and was an unfavorable prognostic biomarker for CC and HNSCC.

LRP1B mutations are associated with favorable outcomes to immune checkpoint inhibitors across multiple cancer types

BACKGROUND

Low-density lipoprotein receptor-related protein 1b (encoded by LRP1B) is a putative tumor suppressor, and preliminary evidence suggests LRP1B-mutated cancers may have improved outcomes with immune checkpoint inhibitors (ICI).

METHODS

We conducted a multicenter, retrospective pan-cancer analysis of patients with LRP1B alterations treated with ICI at Duke University, Johns Hopkins University (JHU) and University of Michigan (UM). The primary objective was to assess the association between overall response rate (ORR) to ICI and pathogenic or likely pathogenic (P/LP) LRP1B alterations compared with LRP1B variants of unknown significance (VUS). Secondary outcomes were the associations with progression-free survival (PFS) and overall survival (OS) by LRP1B status.

RESULTS

We identified 101 patients (44 Duke, 35 JHU, 22 UM) with LRP1B alterations who were treated with ICI. The most common tumor types by alteration (P/LP vs VUS%) were lung (36% vs 49%), prostate (9% vs 7%), sarcoma (5% vs 7%), melanoma (9% vs 0%) and breast cancer (3% vs 7%). The ORR for patients with LRP1B P/LP versus VUS alterations was 54% and 13%, respectively (OR 7.5, 95% CI 2.9 to 22.3, p=0.0009). P/LP LRP1B alterations were associated with longer PFS (HR 0.42, 95% CI 0.26 to 0.68, p=0.0003) and OS (HR 0.62, 95% CI 0.39 to 1.01, p=0.053). These results remained consistent when excluding patients harboring microsatellite instability (MSI) and controlling for tumor mutational burden (TMB).

CONCLUSIONS

This multicenter study shows significantly better outcomes with ICI therapy in patients harboring P/LP versus VUS LRP1B alterations, independently of TMB/MSI status. Further mechanistic and prospective validation studies are warranted.

A comprehensive analysis of somatic alterations in Chinese ovarian cancer patients

Ovarian cancer is one of the most common cancers in women and is often diagnosed as advanced stage because of the subtle symptoms of early ovarian cancer. To identify the somatic alterations and new biomarkers for the diagnosis and targeted therapy of Chinese ovarian cancer patients, a total of 65 Chinese ovarian cancer patients were enrolled for detection of genomic alterations. The most commonly mutated genes in ovarian cancers were TP53 (86.15%, 56/65), NF1 (13.85%, 9/65), NOTCH3 (10.77%, 7/65), and TERT (10.77%, 7/65). Statistical analysis showed that TP53 and LRP1B mutations were associated with the age of patients, KRAS, TP53, and PTEN mutations were significantly associated with tumor differentiation, and MED12, LRP2, PIK3R2, CCNE1, and LRP1B mutations were significantly associated with high tumor mutational burden. The mutation frequencies of LRP2 and NTRK3 in metastatic ovarian cancers were higher than those in primary tumors, but the difference was not significant (P = 0.072, for both). Molecular characteristics of three patients responding to olapanib supported that BRCA mutation and HRD related mutations is the target of olaparib in platinum sensitive patients. In conclusion we identified the somatic alterations and suggested a group of potential biomarkers for Chinese ovarian cancer patients. Our study provided a basis for further exploration of diagnosis and molecular targeted therapy for Chinese ovarian cancer patients.

Genomic Copy Number Variation Study of Nine Macaca Species Provides New Insights into Their Genetic Divergence, Adaptation, and Biomedical Application

Copy number variation (CNV) can promote phenotypic diversification and adaptive evolution. However, the genomic architecture of CNVs among Macaca species remains scarcely reported, and the roles of CNVs in adaptation and evolution of macaques have not been well addressed. Here, we identified and characterized 1,479 genome-wide hetero-specific CNVs across nine Macaca species with bioinformatic methods, along with 26 CNV-dense regions and dozens of lineage-specific CNVs. The genes intersecting CNVs were overrepresented in nutritional metabolism, xenobiotics/drug metabolism, and immune-related pathways. Population-level transcriptome data showed that nearly 46% of CNV genes were differentially expressed across populations and also mainly consisted of metabolic and immune-related genes, which implied the role of CNVs in environmental adaptation of Macaca. Several CNVs overlapping drug metabolism genes were verified with genomic quantitative polymerase chain reaction, suggesting that these macaques may have different drug metabolism features. The CNV-dense regions, including 15 first reported here, represent unstable genomic segments in macaques where biological innovation may evolve. Twelve gains and 40 losses specific to the Barbary macaque contain genes with essential roles in energy homeostasis and immunity defense, inferring the genetic basis of its unique distribution in North Africa. Our study not only elucidated the genetic diversity across Macaca species from the perspective of structural variation but also provided suggestive evidence for the role of CNVs in adaptation and genome evolution. Additionally, our findings provide new insights into the application of diverse macaques to drug study.

Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform

Background

The aim of gene expression-based clinical modelling in tumorigenesis is not only to accurately predict the clinical endpoints, but also to reveal the genome characteristics for downstream analysis for the purpose of understanding the mechanisms of cancers. Most of the conventional machine learning methods involved a gene filtering step, in which tens of thousands of genes were firstly filtered based on the gene expression levels by a statistical method with an arbitrary cutoff. Although gene filtering procedure helps to reduce the feature dimension and avoid overfitting, there is a risk that some pathogenic genes important to the disease will be ignored.

Results

In this study, we proposed a novel deep learning approach by combining a convolutional neural network with stationary wavelet transform (SWT-CNN) for stratifying cancer patients and predicting their clinical outcomes without gene filtering based on tumor genomic profiles. The proposed SWT-CNN overperformed the state-of-art algorithms, including support vector machine (SVM) and logistic regression (LR), and produced comparable prediction performance to random forest (RF). Furthermore, for all the cancer types, we firstly proposed a method to weight the genes with the scores, which took advantage of the representative features in the hidden layer of convolutional neural network, and then selected the prognostic genes for the Cox proportional-hazards regression. The results showed that risk stratifications can be effectively improved by using the identified prognostic genes as feature, indicating that the representative features generated by SWT-CNN can well correlate the genes with prognostic risk in cancers and be helpful for selecting the prognostic gene signatures.

Conclusions

Our results indicated that gene expression-based SWT-CNN model can be an excellent tool for stratifying the prognostic risk for cancer patients. In addition, the representative features of SWT-CNN were validated to be useful for evaluating the importance of the genes in the risk stratification and can be further used to identify the prognostic gene signatures.

LDL, HDL and endocrine-related cancer: From pathogenic mechanisms to therapies

Cholesterol is essential for a variety of functions in endocrine-related cells, including hormone and steroid production. We have reviewed the progress to date in research on the role of the main cholesterol-containing lipoproteins; low-density lipoprotein (LDL) and high-density lipoprotein (HDL), and their impact on intracellular cholesterol homeostasis and carcinogenic pathways in endocrine-related cancers. Neither LDL-cholesterol (LDL-C) nor HDL-cholesterol (HDL-C) was consistently associated with endocrine-related cancer risk. However, preclinical studies showed that LDL receptor plays a critical role in endocrine-related tumor cells, mainly by enhancing circulating LDL-C uptake and modulating tumorigenic signaling pathways. Although scavenger receptor type BI-mediated uptake of HDL could enhance cell proliferation in breast, prostate, and ovarian cancer, these effects may be counteracted by the antioxidant and anti-inflammatory properties of HDL. Moreover, 27-hydroxycholesterol a metabolite of cholesterol promotes tumorigenic processes in breast and epithelial thyroid cancer. Furthermore, statins have been reported to reduce the incidence of breast, prostate, pancreatic, and ovarian cancer in large clinical trials, in part because of their ability to lower cholesterol synthesis. Overall, cholesterol homeostasis deregulation in endocrine-related cancers offers new therapeutic opportunities, but more mechanistic studies are needed to translate the preclinical findings into clinical therapies.

Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

Recurrent gene mutations detected in canine mast cell tumours by next generation sequencing

Genetic causes of canine mast cell tumours (MCTs), except for mutations in the KIT gene detected in some MCTs, are generally unknown. We used whole exome sequencing to reveal mutation spectra in canine MCTs. We detected somatic mutations in 87 genes including 10 genes recognized as human cancer drivers. Besides KIT, 14 other genes were recurrently mutated. Subsequently, we performed next generation sequencing of a panel of 50 selected genes in additional MCT samples. In this group, the most frequently altered gene was GNB1 showing a recurrent dinucleotide substitution at position of Gly116 in 30% of the MCT samples (n = 6/20) and Ile80 substitution accompanied by a splice region mutation in one case. We extended the study by analysis of the above mentioned GNB1 regions in additional MCT samples by Sanger sequencing, and assessed the overall prevalence of GNB1 mutations to 17.3% (n = 14/81), which is similar to the prevalence of KIT alterations. Our results indicate that GNB1 mutations are probably involved in canine MCT pathogenesis in both cutaneous and subcutaneous MCT cases. As opposed to KIT alterations, the presence of GNB1 mutations did not negatively affect survival times, and our data even showed a trend towards positive prognosis. If our results are confirmed in a larger number of MCTs, an extension of molecular testing of canine MCTs by GNB1 analysis would help to refine the molecular stratification of MCTs, and become useful for targeted treatment strategies.

Integrated Genomic, Epigenomic, and Expression Analyses of Ovarian Cancer Cell Lines

To improve our understanding of ovarian cancer, we performed genome-wide analyses of 45 ovarian cancer cell lines. Given the challenges of genomic analyses of tumors without matched normal samples, we developed approaches for detection of somatic sequence and structural changes and integrated these with epigenetic and expression alterations. Alterations not previously implicated in ovarian cancer included amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and TGF-beta receptor pathway members, and rearrangements of YAP1-MAML2 and IKZF2-ERBB4. Dose-response analyses to targeted therapies revealed unique molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, MYC amplifications to PARP inhibitor BMN673, and SMAD3/4 alterations to MEK inhibitor MEK162. Genome-wide rearrangements provided an improved measure of sensitivity to PARP inhibition. This study provides a comprehensive and broadly accessible resource of molecular information for the development of therapeutic avenues in ovarian cancer.

The overall survival of patients with late-stage ovarian cancer is dismal. To identify therapeutic opportunities, Papp et al. integrate genomic, epigenomic, and expression analyses to provide a resource of molecular abnormalities in ovarian cancer cell lines and use these to identify tumors sensitive to PARP, MEK, and PI3K inhibitors.

Molecular profiles of BRCA1-associated ovarian cancer treated by platinum-based therapy: Analysis of primary, residual and relapsed tumors

Our study aimed to analyze the evolution of molecular portraits of BRCA1-driven ovarian cancer (OC) during treatment. BRCA1 loss-of-heterozygosity status (LOH) and exome profiles were investigated in serial OC samples from 13 patients, which included primary tumors (n = 11) obtained before neoadjuvant therapy (NACT) or at primary debulking surgery, residual post-NACT cancer tissues (n = 13) and tumor relapses (16 samples from 13 patients). Loss of the wild-type BRCA1 allele was detected in 11/11 (100%) primary tumors, 6/13 (46%) residual post-NACT OC samples and 15/16 (94%) OC relapses. Full tumor triplets were available for four patients undergoing NACT; whereas primary carcinomas from these patients demonstrated BRCA1 LOH, the retention of the wild-type allele was detected in all four post-NACT residual tumors. These four women provided to the study 5 recurrent OC samples; 4 out of 5 tumor relapses had BRCA1 LOH thus resembling BRCA1 status observed in primary but not residual OC tissues. TP53 mutation was detected in 12 out of 13 patients and was retained across all serial samples. OC relapses tended to acquire additional intragenic mutations in genes involved in cell migration, adhesion and cell junction assembly. BRCA1-driven OCs demonstrate the plasticity of BRCA1 status during the treatment course. NACT results in rapid selection of pre-existing BRCA1-proficient cells. However, BRCA1 proficiency appears to be disadvantageous in the absence of platinum exposure, as tumor relapses usually re-acquire BRCA1 LOH during therapy holidays.

Molecular characterization of endometrial cancer and therapeutic implications

PURPOSE OF REVIEW

The present article reviews genomic subtyping of endometrial carcinoma and new molecular markers with therapeutic and prognostic implications.

RECENT FINDINGS

Endometrial cancer has historically been classified through histology into endometrioid (type 1) and nonendometrioid (type II, mainly serous) subtypes. Molecular classification through genomic analysis now allows for a major advance in characterization; four distinct subgroups have been identified: polymerase ε (POLE) ultramutated, microsatellite unstable, copy number low/microsatellite stable, and copy number high/'serous-like'. These subtypes have prognostic implications and may aid in the identification of early-stage patients who are at high risk for recurrence. Through analysis of surrogate markers (POLE, MSI, and p53) and other validated molecular alterations (L1CAM), it may be possible to obtain an integrated molecular risk profile. Ongoing studies are utilizing this risk profile in order to identify patients who may benefit from additional treatment for early-stage disease.

SUMMARY

Molecular characterization of endometrial cancer into subgroups has prognostic and therapeutic implications. Further development of an integrated molecular risk profile may identify patients who could benefit from additional treatment because of a higher risk of recurrence.

Comprehensive genomic sequencing of paired ovarian cancers reveals discordance in genes that determine clinical trial eligibility

OBJECTIVE

We analyzed comprehensive genomic sequencing results from paired ovarian cancer samples to identify changes in mutational events over time.

METHODS

DNA from paired FFPE tumor samples from 50 ovarian cancer patients in the Clearity Foundation Data Repository was analyzed for genomic mutations (GM), copy number alterations (CNA), microsatellite status (MS), tumor mutation burden (TMB), and loss of heterozygosity (LOH) by hybrid-capture, next-generation sequencing of up to 315 genes. Genomic profiles were compared between samples from the same patient. Poor quality results excluded 6 pairs from all analyses and 9 from CNA or LOH.

RESULTS

Forty-four patients with predominantly advanced stage disease (34, 77%) and serous histology (31, 70%) received a median of 3 intervening treatment regimens (range 1-13). Analysis of 22 primary and recurrent sample pairs and 22 recurrent tumor pairs detected a median of 2 GM (range 0-5) and 1 CNA (range 0-6)/sample. TMB, MS, and LOH results were mostly concordant across paired samples. GM were consistent across most pairs [32/44 (73%) concordant], while CNA concordance was less [18/35 (51%)]. No changes were detected in therapeutically relevant GM, but 23% of patients had GM or CNA in the second sample that affect clinical trial eligibility.

CONCLUSIONS

Paired ovarian cancer samples demonstrate stable genomic alterations across time. However, discordance was observed for some genes used as eligibility criteria for molecularly targeted clinical trials. Repeat tumor testing may be useful in cases where eligibility for such trials is deemed important after consideration of testing costs and potential clinical benefit.

Individual Differences in the Response of Human β-Lymphoblastoid Cells to the Cytotoxic, Mutagenic, and DNA-Damaging Effects of a DNA Methylating Agent, N-Methylnitrosourethane

Metabolic activation of many carcinogens leads to formation of reactive intermediates that form DNA adducts. These adducts are cytotoxic when they interfere with cell division. They can also cause mutations by miscoding during DNA replication. Therefore, an individual's risk of developing cancer will depend on the balance between these processes as well as their ability to repair the DNA damage. Our hypothesis is that variations of genes participating in DNA damage repair and response pathways play significant roles in an individual's risk of developing tobacco-related cancers. To test this hypothesis, 61 human B-lymphocyte cell lines from the International HapMap project were phenotyped for their sensitivity to the cytotoxic and genotoxic properties of a model methylating agent, N-nitroso-N-methylurethane (NMUr). Cell viability was measured using a luciferase-based assay. Repair of the mutagenic and toxic DNA adduct, O⁶-methylguanine (O⁶-mG), was monitored by LC-MS/MS analysis. Genotoxic potential of NMUr was assessed employing a flow-cytometry based in vitro mutagenesis assay in the phosphatidylinositol-glycan biosynthesis class-A (PIG-A) gene. A wide distribution of responses to NMUr was observed with no correlation to gender or ethnicity. While the rate of O⁶-mG repair partially influenced the toxicity of NMUr, it did not appear to be the major factor affecting individual susceptibility to the mutagenic effects of NMUr. Genome-wide analysis identified several novel single nucleotide polymorphisms to be explored in future functional validation studies for a number of the toxicological end points.

Comprehensive genomic profiling of small cell lung cancer in Chinese patients and the implications for therapeutic potential

Background

Small cell lung cancer (SCLC) is one of the deadliest malignancies and accounts for nearly 15% of lung cancers. Previous study had revealed the genomic characterization of SCLC in Western patients. However, little is known about that in Chinese SCLC patients.

Methods

Formalin‐fixed paraffin‐embedded tumor tissues and matched blood samples from 122 Chinese SCLC patients were collected for next generation sequencing to detect 450 cancer‐related genes. All pathological diagnoses were confirmed by independent pathologists.

Results

The most frequently altered genes were TP53 (93.4%), RB1 (78.7%), LRP1B (18.9%), KMT2D (15.6%), FAT1 (11.5%), KMT2C (11.5%), SPTA1 (11.5%), STK24 (11.5%), FAM135B (10.7%), and NOTCH1 (10.7%). The gene fusion/rearrangement detection rate was 16.4%, and mostly occurred in chromosomes 7 and 17. The rate of co‐occurring mutations of TP53 and RB1 in these Chinese SCLC patients was 74.6%, and lower than the reported Western patients (90.9%, P = 0.007). The most common gene mutations (83.6%) were found in cell cycle signaling pathway in Chinese SCLC patients. Mutation of Wnt and Notch signaling pathways in the Chinese cohort were lower than Western cohort (P = 0.0013 and 0.0068). A significant association was found between high tumor mutation burden and mutations involved in FAT1, TP53, SPTA1, KEAP1, KMT2D, MAGI2, NOTCH2, NOTCH3, FLT1, KDM6A, and FAT4.

Conclusions

In this study, we characterized the genomic alterations profile of Chinese SCLC patients. Compared with westerners, the genetic alterations of Chinese SCLC patients presented different patterns. Our data might provide useful information in targeted therapy and drug development for Chinese SCLC patients.

Association of LRP1B Mutation With Tumor Mutation Burden and Outcomes in Melanoma and Non-small Cell Lung Cancer Patients Treated With Immune Check-Point Blockades

Background: Tumor mutation burden (TMB) have been served as the most prevalent biomarkers to predict immunotherapy response. LRP1B (low-density lipoprotein receptor-related protein 1B) is frequently mutated in melanoma, non-small cell lung cancer (NSCLC) and other tumors; however, its association with TMB and survival in patients with immunotherapy remains unknown.

Methods: We curated somatic mutation data and clinicopathologic information from 332 melanoma immunotherapy samples for discovery and 113 NSCLC samples for further corroboration. Bayesian variants non-negative matrix factorization was used to extract tumor mutational signatures. Multivariate Cox and logistic regression models were applied to adjust confounding factors. The CIBERSORT and GSEA algorithm were separately used to infer leukocyte relative abundance and significantly enriched pathways.

Results: Patients with LRP1B mutation were identified to be associated with prolonged survival in both immunotherapy cohort. Higher tumor mutation burden was found in LRP1B mutated patients, and the association remained significant after controlling for age, gender, stage, mutations in TP53 and ATR, and mutational signatures. Immune response and cell cycle regulation circuits were among the top enriched pathways in samples with LRP1B mutations.

Conclusion: Our studies suggested sequencing even a single, frequently mutated gene may provide insight into genome-wide mutational burden, and may serve as a biomarker to predict immune response.

miR-500 promotes cell proliferation by directly targetting LRP1B in prostate cancer

Accumulating evidence suggests that miRNAs play a crucial role in the development of prostate cancer (PC); however, the role of miR-500 in PC remains poorly understood. The data presented here reveal abnormal increases in miR-500 expression in PC tissues and cell lines. Suppression of miR-500 expression significantly inhibited the proliferation of PC-3 and LnCap cells and was negatively regulative with low-density lipoprotein receptor-related protein 1B (LRP1B). Increased cell cycle arrest at the G1 stage and decreased protein expression of cyclinD1 and CDK2 was observed in response to miR-500 knockdown in PC-3 and LnCap cells, in combination with LRP1B overexpression. LRP1B was identified as a target of miR-500 and was significantly decreased in PC tissues. Taken together, these findings demonstrate that miR-500 plays an important role in the proliferation of PC cells via the inhibition of LRP1B expression.

Multiple ABCB1 transcriptional fusions in drug resistant high-grade serous ovarian and breast cancer

ABCB1 encodes Multidrug Resistance protein (MDR1), an ATP-binding cassette member involved in the cellular efflux of chemotherapeutic drugs. Here we report that ovarian and breast samples from chemotherapy treated patients are positive for multiple transcriptional fusions involving ABCB1, placing it under the control of a strong promoter while leaving its open reading frame intact. We identified 15 different transcriptional fusion partners involving ABCB1, as well as patients with multiple distinct fusion events. The partner gene selected depended on its structure, promoter strength, and chromosomal proximity to ABCB1. Fusion positivity was strongly associated with the number of lines of MDR1-substrate chemotherapy given. MDR1 inhibition in a fusion positive ovarian cancer cell line increased sensitivity to paclitaxel more than 50-fold. Convergent evolution of ABCB1 fusion is therefore frequent in chemotherapy resistant recurrent ovarian cancer. As most currently approved PARP inhibitors (PARPi) are MDR1 substrates, prior chemotherapy may precondition resistance to PARPi.

ABCB1 encodes Multidrug Resistance Protein which promotes efflux of chemotherapeutic and targeted agents. Here, in breast and ovarian cancer the authors identify multiple transcriptional fusion partners involving ABCB1 that are associated with treatment failure and previous treatment regimens.

Histone deacetylase 2 regulates the doxorubicin (Dox) resistance of hepatocarcinoma cells and transcription of ABCB1

Histone deacetylases (HDACs) can regulate cell-cycle, differentiation, and apoptosis of hepatocarcinoma (HCC) cells, while their roles in drug sensitivity remain unclear. Our results showed that the expression of HDAC2 was significantly increased in HCC doxorubicin (Dox) resistant cells as compared with their corresponding control cells. Over expression of HDAC2 can increase the cell viability and decrease the Dox sensitivity. Kaplan-Meier Plotter assay revealed that HCC patients with higher levels of HDAC2 had significantly poor prognosis than that of the lower expression patients. Mechanistically studies revealed that HDAC2 can regulate the transcription of ABCB1 via directly binding with its promoter and increasing its expression in Dox resistant HCC cells. Knockdown of HDAC2 significantly inhibited the expression of ABCB1. Co-immunoprecipitation revealed that HDAC2 can bind with c-fos, an important transcription factor of ABCB1, in HCC/Dox cells. Knockdown of c-Fos decreased the binding between HDAC2 and promoter of ABCB1 in HCC/Dox cells. Collectively, our data revealed that HDAC2 can regulate Dox sensitivity of HCC cells and the transcription of ABCB1.

Systematic analysis reveals molecular characteristics of ERG-negative prostate cancer

The TMPRSS2:ERG gene fusion is the most prevalent early driver gene activation in prostate cancers of European ancestry, while the fusion frequency is much lower in Africans and Asians. The genomic characteristics and mechanisms for patients lacking ERG fusion are still unclear. In this study, we systematically compared the characteristics of gene fusions, somatic mutations, copy number alterations and gene expression signatures between 201 ERG fusion positive and 296 ERG fusion negative prostate cancer samples. Both common and group-specific genomic alterations were observed, suggesting shared and different mechanisms of carcinogenesis in prostate cancer samples with or without ERG fusion. The genomic alteration patterns detected in ERG-negative group showed similarities with 77.5% of tumor samples of African American patients. These results emphasize that genomic and gene expression features of the ERG-negative group may provide a reference for populations with lower ERG fusion frequency. While the overall expression patterns were comparable between ERG-negative and ERG-positive tumors, we found that genomic alterations could affect the same pathway through distinct genes in the same pathway in both groups of tumor types. Altogether, the genomic and molecular characteristics revealed in our study may provide new opportunities for molecular stratification of ERG-negative prostate cancers.

Single nucleotide variant profiles of viable single circulating tumour cells reveal CTC behaviours in breast cancer

Circulating tumour cell (CTC) behaviours are distinct from those of bulk tissues. Thus, treatments to eliminate CTCs differ from the regimens followed to reduce the primary tumour and its metastases. Accordingly, comprehensively deciphering the single nucleotide variant (SNV) profiles in CTCs, which partially determine CTC behaviours, is a priority. Using viable CTCs isolated with the oHSV1-hTERT-GFP virus coupled with fluorescence-activated cell sorting (FACS), the whole genome was amplified using the multiple annealing and looping-based amplification cycle (MALBAC) method. CTC behaviours were evaluated using the SNVs found to be recurrently mutated in different cells (termed CTC-shared SNVs). Analysis of the sequencing data of 11 CTCs from 8 patients demonstrated that SNVs accumulated sporadically among CTCs and their matched primary tumours (22 co-occurring mutated genes were identified in the exomes of CTCs and their matched primary tissues and metastases), and 394 SNVs were shared by at least two CTCs. Mutated APC and LRP1B genes co-occurred in CTC-shared and bulk-tissue SNVs. Additionally, the breast-originating identity of the CTC-shared SNVs was verified, and they demonstrated the following CTC behaviours: i) intravasation competency; ii) increased migration or motility; iii) enhanced cell-cell interactions; iv) variation in energy metabolism; v) an activated platelet or coagulation system; and vi) dysfunctional mitosis. These results demonstrated that it is feasible to capture and amplify the genomes of single CTCs using the described pipeline. CTC-shared SNVs are a potential signature for identifying the origin of the primary tumour in a liquid biopsy. Furthermore, CTCs demonstrated some behaviours that are unique from those of bulk tissues. Therefore, therapies to eradicate these precursors of metastasis may differ from the existing traditional regimens.

Expression of a recombinant full-length LRP1B receptor in human non-small cell lung cancer cells confirms the postulated growth-suppressing function of this large LDL receptor family member

Low-density lipoprotein (LDL) receptor-related protein 1B (LRP1B), a member of the LDL receptor family, is frequently inactivated in multiple malignancies including lung cancer. LRP1B is therefore considered as a putative tumor suppressor. Due to its large size (4599 amino acids), until now only minireceptors or receptor fragments have been successfully cloned. To assess the effect of LRP1B on the proliferation of non-small cell lung cancer cells, we constructed and expressed a transfection vector containing the 13.800 bp full-length murine Lrp1b cDNA using a PCR-based cloning strategy. Expression of LRP1B was analyzed by quantitative RT-PCR (qRT-PCR) using primers specific for human LRP1B or mouse Lrp1b. Effective expression of the full length receptor was demonstrated by the appearance of a single 600 kDa band on Western Blots of HEK 293 cells. Overexpression of Lrp1b in non-small cell lung cancer cells with low or absent endogenous LRP1B expression significantly reduced cellular proliferation compared to empty vector-transfected control cells. Conversely, in Calu-1 cells, which express higher endogenous levels of the receptor, siRNA-mediated LRP1B knockdown significantly enhanced cellular proliferation. Taken together, these findings demonstrate that, consistent with the postulated tumor suppressor function, overexpression of full-length Lrp1b leads to impaired cellular proliferation, while LRP1B knockdown has the opposite effect. The recombinant Lrp1b construct represents a valuable tool to unravel the largely unknown physiological role of LRP1B and its potential functions in cancer pathogenesis.

Regulatory network involving miRNAs and genes in serous ovarian carcinoma

Serous ovarian carcinoma (SOC) is one of the most life-threatening types of gynecological malignancy, but the pathogenesis of SOC remains unknown. Previous studies have indicated that differentially expressed genes and microRNAs (miRNAs) serve important functions in SOC. However, genes and miRNAs are identified in a disperse form, and limited information is known about the regulatory association between miRNAs and genes in SOC. In the present study, three regulatory networks were hierarchically constructed, including a differentially-expressed network, a related network and a global network to reveal associations between each factor. In each network, there were three types of factors, which were genes, miRNAs and transcription factors that interact with each other. Focus was placed on the differentially-expressed network, in which all genes and miRNAs were differentially expressed and therefore may have affected the development of SOC. Following the comparison and analysis between the three networks, a number of signaling pathways which demonstrated differentially expressed elements were highlighted. Subsequently, the upstream and downstream elements of differentially expressed miRNAs and genes were listed, and a number of key elements (differentially expressed miRNAs, genes and TFs predicted using the P-match method) were analyzed. The differentially expressed network partially illuminated the pathogenesis of SOC. It was hypothesized that if there was no differential expression of miRNAs and genes, SOC may be prevented and treatment may be identified. The present study provided a theoretical foundation for gene therapy for SOC.

RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential

Based on high-throughput sequencing technology, the detection of gene fusions is no longer a big challenge but estimating the oncogenic potential of fusion genes remains challenging. Recent studies successfully applied machine learning methods and gene structural and functional features of fusion mutation to predict their oncogenic potentials. However, the transcription characterizations features of fusion genes have not yet been studied. In this study, based on the clonal evolution theory, we hypothesized that a fusion gene is more likely to be an oncogenic genomic alteration, if the neoplastic cells harboring this fusion mutation have larger clonal size than other neoplastic cells in a tumor. We proposed a novel method, called iFCR (internal Fusion Clone Ratio), given an estimation of oncogenic potential for fusion mutations. We have evaluated the iFCR method in three public cancer transcriptome sequencing datasets; the results demonstrated that the fusion mutations occurring in tumor samples have higher internal fusion clone ratio than normal samples. And the most frequent prostate cancer fusion mutation, TMPRSS2-ERG, appears to have a remarkably higher iFCR value in all three independent patients. The preliminary results suggest that the internal fusion clone ratio might potentially advantage current fusion mutation oncogenic potential prediction methods.