Clinical implications of single cell sequencing for bladder cancer.

Bladder cancer (BC) is the 10th most common cancer worldwide, with about 0.5 million reported new cases and about 0.2 million deaths per year. In this scoping review, we summarize the current evidence regarding the clinical implications of single-cell sequencing for bladder cancer based on PRISMA guidelines. We searched PubMed, CENTRAL, Embase, and supplemented with manual searches through the Scopus, and Web of Science for published studies until February 2023. We included original studies that used at least one single-cell technology to study bladder cancer. Forty-one publications were included in the review. Twenty-nine studies showed that this technology can identify cell subtypes in the tumor microenvironment that may predict prognosis or response to immune checkpoint inhibition therapy. Two studies were able to diagnose BC by identifying neoplastic cells through single-cell sequencing urine samples. The remaining studies were mainly a preclinical exploration of tumor microenvironment at single cell level. Single-cell sequencing technology can discriminate heterogeneity in bladder tumor cells and determine the key molecular properties that can lead to the discovery of novel perspectives on cancer management. This nascent tool can advance the early diagnosis, prognosis judgment, and targeted therapy of bladder cancer.

Bioinformatic analysis of single-cell RNA sequencing dataset dissects cellular heterogeneity of triple-negative breast cancer in transcriptional profile, splicing event and crosstalk network.

BACKGROUND: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high tumoral heterogeneity, while the detailed regulatory network is not well known. METHODS: Via single-cell RNA-sequencing (scRNA-seq) data analysis, we comprehensively investigated the transcriptional profile of different subtypes of TNBC epithelial cells with gene regulatory network (GRN) and alternative splicing (AS) event analysis, as well as the crosstalk between epithelial and non-epithelial cells. RESULTS: Of note, we found that luminal progenitor subtype exhibited the most complex GRN and splicing events. Besides, hnRNPs negatively regulates AS events in luminal progenitor subtype. In addition, we explored the cellular crosstalk among endothelial cells, stromal cells and immune cells in TNBC and discovered that NOTCH4 was a key receptor and prognostic marker in endothelial cells, which provide potential biomarker and target for TNBC intervention. CONCLUSIONS: In summary, our study elaborates on the cellular heterogeneity of TNBC, revealing that NOTCH4 in endothelial cells was critical for TNBC intervention. This in-depth understanding of epithelial cell and non-epithelial cell network would provide theoretical basis for the development of new drugs targeting this sophisticated network in TNBC.

Does focal heterogeneity affect survival in postoperative ipsilateral multifocal and multicentric breast cancers?

SUMMARY OBJECTIVE: In multicentric/multifocal breast tumors, there may be immunological and histological differences between foci that may affect survival and treatment choice. We aimed to evaluate the effect of focal heterogeneity seen in multicentric/multifocal breast tumors on survival. METHODS: We retrospectively collected and analyzed the clinicopathological data of 89 female patients with multifocal/multicentric breast cancer, whose surgical and medical treatment was completed and who were followed up for 5 years. RESULTS: Of all patients, 29.2% (26/89) were heterogeneous. Heterogeneity of these foci was as follows: histologic heterogeneity of index foci (mix type): 15.7% (14/89), histologic heterogeneity of inter-foci: 7.9% (7/89), and immunohistochemical heterogeneity of inter-foci: 10.1% (9/89). When additional foci were evaluated, oncological therapy was changed for 3 (3.3%) of 89 patients. Heterogeneity does not have a significant (p>0.05) effect on recurrence and survival in multicentric/multifocal breast cancers. Pathological N stage is an independent risk factor for disease-free survival (hazard ratio=2.29, 95% confidence interval=1.39-3.76, p=0.001). CONCLUSIONS: In multifocal/multicentric breast cancers, less than 4% of patients may experience heterogeneity requiring change in the therapeutic decision. However, heterogeneity does not have a significant effect on recurrence and survival in multifocal/multicentric breast cancers. The pathological N stage is an independent risk factor for disease-free survival.

Brain Tumor Heterogeneity

Tumor heterogeneity is the concept that different tumor cells provide distinct biomorphological lesions, gene expressions, proliferation, microenvironment and graduated capacity of metastatic lesions. Brain tumor heterogeneity has been recently discussed about the interesting interaction of chronic inflammation, microenvironment, epigenetics and glioma steam cells. Brain tumors remain a challenge with regards to medication and disease, due to the lack of treatment options and unsatisfactory results. These results might be the result of the brain tumor heterogeneity and its multiple resistance mechanisms to chemo and radiotherapy.

Prostate Cancer Spheroids: A Three-Dimensional Model for Studying Tumor Heterogeneity.

Prostate cancer is one of the main causes of cancer and the sixth cause of death among men worldwide. One of the major challenges in prostate cancer research is cell heterogeneity defined as the different genomic and phenotypic characteristics in each individual cell making more difficult to assess the proper prostate cancer diagnosis and therapy. Tumor 3D spatial arrangement allow a strong interaction between the different cellular lineages and components which modulate cell proliferation, differentiation, and morphology. Prostate cancer spheroids are a cellular model which is capable to mimic the mechanical tensions of tumor tissue, providing a more representative pathophysiological model than the use of conventional 2D culture. Here, we describe a protocol to develop a 3D model of spheroids using prostate cancer cell lines (LNCaP, PC3, VCaP) which can be used to improve research considering tumoral heterogeneity role in cancer development, prognosis, and therapy.

Photodynamic therapy of Glioblastoma cells using doped conjugated polymer nanoparticles: An in vitro comparative study based on redox status.

Due to their superb light absorption and photostability conjugated polymer nanoparticles are promising photosensitizers (PS) for their use in Photodynamic therapy (PDT). Recently, we developed metallated porphyrin-doped conjugated polymer nanoparticles (CPNs) for PDT that efficiently eliminate tumor cells through reactive oxygen species (ROS) mediated photoinduced damage of apoptotic nature. These nanoaggregates act as densely packed multi-chromophoric systems having exceptional light harvesting and (intra-particle) energy transfer capabilities which lead to efficient photosensitized formation of ROS. In general, three key components; light, PS, and oxygen; are considered in the prediction of the PDT outcome. However, recent studies led to the discovery of a profound genetic heterogeneity among glioblastoma (GBM) cells which include the adaptation to ROS. Thus, tumor heterogeneity and their associated difference in sensitivity to ROS-producing therapeutic agents must be considered in the design of PDT protocols for the prediction of its outcome. In this study, anticancer activity through ROS-mediated PDT using CPNs was compared in three GBM cell lines with different initial redox status. T98G cells were the most effective incorporating nanoparticles but also were the most resistant to CPN-PDT effect. In part, this feature could be attributed to the differential basal and PDT-induced antioxidant enzyme levels found in these cells measured by gene expression analysis. Furthermore, considering that cell-specific antioxidant enzyme status is a significant feature of GBM heterogeneity, establishing its correlation with CPN-PDT outcome might be important for designing novel and improved CPN-based treatments.

Discovery of a transcriptomic core of genes shared in 8 primary retinoblastoma with a novel detection score analysis.

PURPOSE: Expression microarrays are powerful technology that allows large-scale analysis of RNA profiles in a tissue; these platforms include underexploited detection scores outputs. We developed an algorithm using the detection score, to generate a detection profile of shared elements in retinoblastoma as well as to determine its transcriptomic size and structure. METHODS: We analyzed eight briefly cultured primary retinoblastomas with the Human transcriptome array 2.0 (HTA2.0). Transcripts and genes detection scores were determined using the Detection Above Background algorithm (DABG). We used unsupervised and supervised computational tools to analyze detected and undetected elements; WebGestalt was used to explore functions encoded by genes in relevant clusters and performed experimental validation. RESULTS: We found a core cluster with 7,513 genes detected and shared by all samples, 4,321 genes in a cluster that was commonly absent, and 7,681 genes variably detected across the samples accounting for tumor heterogeneity. Relevant pathways identified in the core cluster relate to cell cycle, RNA transport, and DNA replication. We performed a kinome analysis of the core cluster and found 4 potential therapeutic kinase targets. Through analysis of the variably detected genes, we discovered 123 differentially expressed transcripts between bilateral and unilateral cases. CONCLUSIONS: This novel analytical approach allowed determining the retinoblastoma transcriptomic size, a shared active transcriptomic core among the samples, potential therapeutic target kinases shared by all samples, transcripts related to inter tumor heterogeneity, and to determine transcriptomic profiles without the need of control tissues. This approach is useful to analyze other cancer or tissue types.

Polysome Profiling of a Human Glioblastoma Reveals Intratumoral Heterogeneity.

Glioblastoma (GBM) is one of the most aggressive cancers, with median survival of less than 2 years. Despite of considerable advance in molecular classification of GBMs, no improvements in therapy have been described. The scenario is further complicated by tumor heterogeneity and the relationship among genetic, transcriptional and functional findings. Classically, gene expression has been evaluated by steady-state mRNA, however, this does not take translational control into consideration, which contributes considerably to the composition of the proteome. In this study, we evaluated the transcriptomic and translatomic signature of a GBM obtained from a single patient focusing in tumor heterogeneity. In a sampling of eight fragments, we investigated the translation rates, mTORC1 and ERK1/2 pathways and identified both total and polysome associated mRNAs. An increased translation rate was observed in fragments with high-grade histological features. High-grade histology was also associated with the expression of genes related to extracellular matrix (ECM) and angiogenesis, in both transcriptomes and translatomes. However, genes associated with epithelial to mesenchymal transition and stress response, were observed only in translatomes from high-grade fragments. Overall, our results demonstrate that isolation of translated mRNA can be used to identify biomarkers and reveal previously unrecognized determinants of heterogeneity in GBMs.

A phenotypical map of disseminated hepatocellular carcinoma suggests clonal constraints in metastatic sites.

AIMS: Access to tissue in patients with hepatocellular carcinoma (HCC) is limited compared to other malignancies, particularly at advanced stages. This has precluded a thorough characterisation of molecular drivers of HCC dissemination, particularly in relation to distant metastases. Biomarker assessment is restricted to early stages, and paired primary-metastatic comparisons between samples from the same patient are difficult. METHODS AND RESULTS: We report the evaluation of 88 patients with HCC who underwent autopsy, including multiregional sampling of primary and metastatic sites totalling 230 nodules analysed. The study included morphological assessment, immunohistochemistry and mutation status of the TERT promoter, the most frequently mutated gene in HCC. We confirm a strong predilection of HCC for lung dissemination, including subclinical micrometastases (unrecognised during imaging and macroscopic examinations) in 30% of patients with disseminated disease. Size of dominant tumour nodule; multinodularity; macrovascular invasion; high histological, nuclear and architectural grades; and cellular crowding were associated with the presence of extrahepatic metastasis. Among the immunohistochemistry markers tested, metastatic nodules had significantly higher K19 and EpCAM expression than primary liver tumours. Morphological and immunohistochemical features showed that metastatic HCC could be traced back to the primary tumour, sometimes to a specific hepatic nodule. CONCLUSIONS: This study suggests limited heterogeneity in metastatic sites compared to primary tumour sites.

Aldo-Keto Reductases as Early Biomarkers of Hepatocellular Carcinoma: A Comparison Between Animal Models and Human HCC.

BACKGROUND: The intrinsic heterogeneity of hepatocellular carcinoma (HCC) represents a great challenge for its molecular classification and for detecting predictive biomarkers. Aldo-keto reductase (Akr) family members have shown differential expression in human HCC, while AKR1B10 overexpression is considered a biomarker; AKR7A3 expression is frequently reduced in HCC. AIMS: To investigate the time-course expression of Akr members in the experimental hepatocarcinogenesis. METHODS: Using DNA-microarray data, we analyzed the time-course gene expression profile from nodules to tumors (4-17 months) of 17 Akr members induced by the resistant hepatocyte carcinogenesis model in the rat. RESULTS: The expression of six members (Akr1c19, Akr1b10, Akr7a3, Akr1b1, Akr1cl1, and Akr1b8) was increased, comparable to that of Ggt and Gstp1, two well-known liver cancer markers. In particular, Akr7a3 and Akr1b10 expression also showed a time-dependent increment at mRNA and protein levels in a second hepatocarcinogenesis model induced with diethylnitrosamine. We confirmed that aldo-keto reductases 7A3 and 1B10 were co-expressed in nine biopsies of human HCC, independently from the presence of glypican-3 and cytokeratin-19, two well-known HCC biomarkers. Because it has been suggested that expression of Akr members is regulated through NRF2 activity at the antioxidant response element (ARE) sequences, we searched and identified at least two ARE sites in Akr1b1, Akr1b10, and Akr7a3 from rat and human gene sequences. Moreover, we observed higher NRF2 nuclear translocation in tumors as compared with non-tumor tissues. CONCLUSIONS: Our results demonstrate that Akr7a3 mRNA and protein levels are consistently co-expressed along with Akr1b10, in both experimental liver carcinogenesis and some human HCC samples. These results highlight the presence of AKR7A3 and AKR1B10 from early stages of the experimental HCC and introduce them as a potential application for early diagnosis, staging, and prognosis in human cancer.

Identificação e anotação funcional de RNAs longos não codificadores associados à subtipos moleculares em tumores pancreáticos / Identification of long non coding RNAs associated to molecular subtypes in pancreatic tumors

O Adenocarcinoma Pancreático Ductal (Pancreatic Ductal Adenocarcinoma - PDAC) é a sé- tima causa de mortes por câncer no mundo, com uma taxa de sobrevida de apenas 6%. Embora alguns genes estejam recorrentemente mutados em grande parte dos tumores e sejam críticos para a oncogênese, a heterogeneidade das alterações moleculares tanto no tumor quanto em componentes do microambiente tumoral se reflete em diferentes características fenotípicas com comportamentos clínicos distintos e que têm sido associados a diferentes subtipos moleculares através da análise computacional de dados de alterações somáticas e transcricionais no PDAC. RNAs não codificadores longos (lncRNAs) têm sido reconhecidos como importantes reguladores da expressão gênica em doenças proliferativas mas sua associação com subtipos em PDAC e sua contribuição para o estabelecimento de diferentes fenótipos moleculares e clínicos da doença não foi explorada até o momento. Neste trabalho, foi implementada uma abordagem computacional com o objetivo de identificar e anotar funcionalmente lncRNAs associados a subtipos moleculares de PDAC. Inicialmente, a classificação não supervisionada por Fatoração Matricial Não Negativa (Non-Negative Matrix Factorization - NMF) de dados de expressão gê- nica global de amostras clínicas disponíveis publicamente (The Cancer Genome Atlas - TCGA) resultou na identificação de quatro subgrupos distintos de PDAC, que recapitulam os fenótipos Exócrino/Endócrino, Imunogênico, Escamoso e Progenitor descritos na literatura. Uma análise de expressão diferencial permitiu a identificação de assinaturas de expressão gênica características que incluem lncRNAs associados a cada subgrupo. Através da construção de redes de coexpressão de mRNAs e lncRNAs e a identificação de módulos da rede significativamente enriquecidos em genes que participam em vias moleculares conhecidas foi possível inferir possíveis funções biológicas à lncRNAs associados aos diferentes subtipos moleculares, tais como funções exócrinas/neuroendócrinas, imunogênicas, reparo de DNA/progressão do ciclo celular e progenitoras/morfogênicas. Entre ele, o subgrupo 3, enriquecido para fenótipo Escamoso e associado a hiper-expressão do supressor tumoral TP63, possui dois lncRNAS hiper-expressos neste subgrupo em relação aos outros subgrupos, sendo que o lncRNA antissenso FAM83A-AS1 tem a predição de interagir com as proteínas FGFR2, AXIN1, PTEN, BRAF, SMAD4, TGFBR2, TP53 e CDKN2A, que exercem funções importantes na transdução de sinal e supressão tumoral no câncer incluindo o de pâncreas. Entre os lncRNAs hipo-regulados no subgrupo 3 em relação ao outros subgrupos, alguns, como FLJ42875, LOC338651, C20orf56 e LOC38838 tem predição de interação com alta afinidade à proteína BRCA2, que está envolvida no reparo de DNA e participa de processos de resistência à quimioterápicos. As informações trazidas por este estudo permitem gerar hipóteses sobre a contribuição de lncRNAs para a definição de subtipos moleculares de PDAC e priorizar candidatos e experimentos para estudos funcionais de modo a contribuir para um melhor entendimento sobre os mecanismos de ação de lncRNAs na tumorigênese e agressividade do câncer de pâncreas

Pancreatic Ductal Adenocarcinoma (PDAC) is the seventh cause of worldwide cancer related deaths, with an overall survival rate of only 6%. Some genes might be recurrently mutated in a large number of tumors, and be critical for oncogenesis, molecular alteration heterogeneity both in the tumor as all as in the tumor microenvironment is reflected in diverse phenotypic features with distinct clinical outcomes, and this distinction in multiple molecular subtypes has been drawn through transcriptional and somatic alteration computational analysis within PDAC. Long Non Coding RNAs (lncRNAs) have been recognized as important gene expression regulators in proliferative diseases, but its association to molecular subtypes in PDAC and its contribution in the establishment of diverse molecular and clinical phenotypes hasnt been explored at length until the present. This work focused on the implementation of a computational approach with the objective of lncRNA identification and functional annotation associated to distinct molecular subtypes in PDAC. Initially, Non-negative Matrix Factorization (NMF), an unsupervised classification method, applied to global gene expression data from publicly available clinical samples (The Cancer Genome Atlas - TCGA) resulted in the identification of four distinct PDAC molecular subgroups reminiscent of Exocrine/Endocrine, Immunogenic, Squamous and Progenitor phenotypes. Differential expression analysis allowed a characteristic gene expression signature identification, including distinct molecular subtype associated lncRNAs. mRNA and lncRNA containing gene co-expression modules significantly enriched annotated pathways containing the molecular subtype associated lncRNAs allowed to designate possible molecular functions of the distinct molecular subtype associated lncRNAs, such as exocrine/neuroendocrine, immunogenic, DNA repair/cell cycle progression and progenitor/morphogenic functions. Subgroup 3, enriched with a Squamous phenotype and associated to TP63 over-expression contains two lncRNAs over-expressed compared to other subgroups; furthermore, the antisense lncRNA FAM83A-AS1 yielded a predicted lncRNA-protein interaction to FGFR2, AXIN1, PTEN, BRAF, SMAD4, TGFBR2, TP53 and CDKN2A, proteins that play important signal transduction and tumor suppressor roles in several cancer types, including pancreas. Among under-expressed lncRNAs in subgroup 3 compared to the other subgroups, some, such as FLJ42875, LOC338651, C20orf56 and LOC38838 yilded a high protein interaction prediction score with BRCA2, a protein involved in DNA repair and processes resuling in chemotherapy resistance. The information brought by this study allowed to generate hypothesis on lncRNA contribution to define PDAC molecular subtypes, helping prioritize candidates and experiments for functional studies, thus contributing to a better understanding on lncRNA mechanisms related to tumor progression and aggressiveness in pancreatic cancer

miRNome landscape analysis reveals a 30 miRNA core in retinoblastoma.

BACKGROUND: miRNAs exert their effect through a negative regulatory mechanism silencing expression upon hybridizing to their target mRNA, and have a prominent position in the control of many cellular processes including carcinogenesis. Previous miRNA studies on retinoblastoma (Rb) have been limited to specific miRNAs reported in other tumors or to medium density arrays. Here we report expression analysis of the whole miRNome on 12 retinoblastoma tumor samples using a high throughput microarray platform including 2578 mature miRNAs. METHODS: Twelve retinoblastoma tumor samples were analyzed using an Affymetrix platform including 2578 mature miRNAs. We applied RMA analysis to normalize raw data, obtained categorical data from detection call values, and also used signal intensity derived expression data. We used Diana-Tools-microT-CDS to find miRNA targets and ChromDraw to map miRNAs in chromosomes. RESULTS: We discovered a core-cluster of 30 miRNAs that were highly expressed in all the cases and a cluster of 993 miRNAs that were uniformly absent in all cases. Another 1022 miRNA were variably present in the samples reflecting heterogeneity between tumors. We explored mRNA targets, pathways and biological processes affected by some of these miRNAs. We propose that the core-cluster of 30 miRs represent miRNA machinery common to all Rb, and affecting most pathways considered hallmarks of cancer. In this core, we identified miR-3613 as a potential and critical down regulatory hub, because it is highly expressed in all the samples and its potential mRNA targets include at least 36 tumor suppressor genes, including RB1. In the variably expressed miRNA, 36 were differentially expressed between males and females. Some of the potential pathways targeted by these 36 miRNAs were associated with hormonal production. CONCLUSION: These findings indicate that Rb tumor samples share a common miRNA expression profile regardless of tumor heterogeneity, and shed light on potential novel therapeutic targets such as mir-3613 This is the first work to delineate the miRNA landscape in retinoblastoma tumor samples using an unbiased approach.

Primary breast cancer cell culture yields intra-tumor heterogeneous subpopulations expressing exclusive patterns of receptor tyrosine kinases.

BACKGROUND: It has become evident that intra-tumor heterogeneity of breast cancer impact on several biological processes such as proliferation, migration, cell death and also might contribute to chemotherapy resistance. The expression of Receptor Tyrosine Kinases (RTKs) has not been analyzed in the context of intra-tumor heterogeneity in a primary breast cancer cell culture. Several subpopulations were isolated from the MBCDF (M serial-breast cancer ductal F line) primary breast cancer cells and were successfully maintained in culture and divided in two groups according to their morphology and RTKs expression pattern, and correlated with biological processes like proliferation, migration, anchorage-independent cell growth, and resistance to cytotoxic chemotherapy drugs and tyrosine kinase inhibitors (TKIs). METHODS: Subpopulations were isolated from MBCDF primary breast cancer cell culture by limiting dilution. RTKs and hormone receptors were examined by Western blot. Proliferation was measure by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide (MTT assay). Cell viability was evaluated by Crystal Violet. Migration was assessed using Boyden chambers. Anchorage-independent cell growth was evaluated by colony formation in soft agar. RESULTS: Several subpopulations were isolated from the MBCDF breast cancer cells that were divided into two groups according to their morphology. Analysis of RTKs expression pattern showed that HER1, HER3, c-Met and VEGFR2 were expressed exclusively in cells from group 1, but not in cells from group 2. PDGFR was expressed only in cells from group 2, but not in cells from group 1. HER2, HER4, c-Kit, IGF1-R were expressed in all subpopulations. Biological processes correlated with the RTKs expression pattern. Group 2 subpopulations present the highest rate of cell proliferation, migration and anchorage-independent cell growth. Analysis of susceptibility to chemotherapy drugs and TKIs showed that only Paclitaxel and Imatinib behaved differently between groups. Group 1-cells were resistant to both Paclitaxel and Imatinib. CONCLUSIONS: We demonstrated that subpopulations from MBCDF primary cell culture could be divided into two groups according to their morphology and a RTKs excluding-expression pattern. The differences observed in RTKs expression correlate with the biological characteristics and chemoresistance of each group. These results suggest that intra-tumor heterogeneity contributes to generate groups of subpopulations with a more aggressive phenotype within the tumor.

Heterogeneidad intratumoral en cáncer de mama: reporte de dos casos y revisión de la literatura / Intratumoral heterogeneity in breast cancer: case report and literature review

El cáncer de mama (CM) es una enfermedad de gran complejidad. Presenta una gran variabilidad molecular, lo cual se puede observar cuando se comparan los tumores de distintos pacientes, dos regiones del mismo tumor, los ganglios regionales comprometidos versus el tumor primario y la metástasis a distancia versus la lesión primaria. Reportamos el caso de dos pacientes con CM con heterogeneidad en el fenotipo tumoral del tumor primario; el primer caso presentó dos tumores simultáneos de diferentes características dentro de la misma mama y el segundo caso mostró variación en el fenotipo del tumor luego del tratamiento neoadyuvante (TN). Así mismo, realizamos un análisis de la información publicada recientemente.

Breast Cancer (BC) is a complex disease. It shows notable molecular differences when we compare tumors from different patients, two intra-tumor distant regions, metastasis in regional lymph node versus primary lesion, and distant metastasis versus primary lesion. We report two cases of BC with tumor phenotype heterogeneity of the primary tumor. The first case developed two different simultaneous lesions inside the same breast and the second one developed a change in tumor phenotype after neoadjuvant treatment. Furthermore, we performed an evaluation of recently published information.