scholarly journals Prediction and analysis of skin cancer progression using genomics profiles of patients

2018 ◽  
Author(s):  
Sherry Bhalla ◽  
Harpreet Kaur ◽  
Anjali Dhall ◽  
Gajendra P. S. Raghava
Keyword(s):  
Cancer Progression ◽  
Primary Tumor ◽  
Prediction Models ◽  
Simple Expression ◽  
The Cancer Genome Atlas ◽  
Machine Learning Techniques ◽  
Validation Dataset ◽  
Metastatic Tumors ◽  
Primary Tumors ◽  
Genomic Features

AbstractMetastatic state of the Skin Cutaneous Melanoma (SKCM) has led to high mortality rate worldwide. Previously, various studies have revealed the association of the metastatic melanoma with the diminished survival rate in comparison to primary tumors. Thus, prediction of melanoma at primary tumor state is crucial to employ optimal therapeutic strategy for prolonged survival of patients. The RNA, miRNA and methylation data of The Cancer Genome Atlas (TCGA) cohort of SKCM is comprehensively analysed to recognize key genomic features that can categorize various states of metastatic tumors from primary tumors with high precision. Subsequently, various prediction models were developed using filtered genomic features implementing various machine learning techniques to classify these primary tumors from metastatic tumors. The SVC model (with class weight and RBF kernel) developed using 17 mRNA features achieved maximum MCC 0.73 with sensitivity, specificity and accuracy 89.19%, 90.48% and 89.47% respectively on independent validation dataset. Our study reveals that gene expression based features performs better than features obtained from miRNA profiling and epigenomic profiling. Our analysis shows that the expression of genesC7, MMP3, KRT14, KRT17, MASP1, and miRNA hsa-mir-205 and hsa-mir-203a are among the key genomic features that may substantially contribute to the oncogenesis of melanoma even on the basis of simple expression threshold. The major prediction models and analysis modules to predict metastatic and primary tumor samples of SKCM are available from a webserver, CancerSPP (http://webs.iiitd.edu.in/raghava/cancerspp/).

scholarly journals Prediction and Analysis of Skin Cancer Progression using Genomics Profiles of Patients

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sherry Bhalla ◽  
Harpreet Kaur ◽  
Anjali Dhall ◽  
Gajendra P. S. Raghava
Keyword(s):  
Cancer Progression ◽  
Cutaneous Melanoma ◽  
Prediction Models ◽  
Survival Rates ◽  
Validation Dataset ◽  
Support Vector ◽  
Melanoma Metastasis ◽  
Primary Tumors ◽  
Genomic Features ◽  
Optimal Therapeutic Strategy

Abstract The metastatic Skin Cutaneous Melanoma (SKCM) has been associated with diminished survival rates and high mortality rates worldwide. Thus, segregating metastatic melanoma from the primary tumors is crucial to employ an optimal therapeutic strategy for the prolonged survival of patients. The SKCM mRNA, miRNA and methylation data of TCGA is comprehensively analysed to recognize key genomic features that can segregate metastatic and primary tumors. Further, machine learning models have been developed using selected features to distinguish the same. The Support Vector Classification with Weight (SVC-W) model developed using the expression of 17 mRNAs achieved Area under the Receiver Operating Characteristic (AUROC) curve of 0.95 and an accuracy of 89.47% on an independent validation dataset. This study reveals the genes C7, MMP3, KRT14, LOC642587, CASP7, S100A7 and miRNAs hsa-mir-205 and hsa-mir-203b as the key genomic features that may substantially contribute to the oncogenesis of melanoma. Our study also proposes genes ESM1, NFATC3, C7orf4, CDK14, ZNF827, and ZSWIM7 as novel putative markers for cutaneous melanoma metastasis. The major prediction models and analysis modules to predict metastatic and primary tumor samples of SKCM are available from a webserver, CancerSPP (http://webs.iiitd.edu.in/raghava/cancerspp/).

scholarly journals Quantification of BRAF V600E alleles predicts papillary thyroid cancer progression

2014 ◽  
Vol 21 (6) ◽  
pp. 891-902 ◽  
Author(s):  
Min-Hee Kim ◽  
Ja Seong Bae ◽  
Dong-Jun Lim ◽  
Hyoungnam Lee ◽  
So Ra Jeon ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Cancer Progression ◽  
Tumour Size ◽  
External Validation ◽  
Allelic Frequency ◽  
The Cancer Genome Atlas ◽  
Braf V600e ◽  
Validation Dataset ◽  
Papillary Thyroid ◽  
Additional Information

The BRAF V600E mutation is the most common genetic alteration in thyroid cancer. However, its clinicopathological significance and clonal mutation frequency remain unclear. To clarify the inconsistent results, we investigated the association between the allelic frequency of BRAF V600E and the clinicopathological features of classic papillary thyroid carcinoma (PTC). Tumour tissues from two independent sets of patients with classic PTC were manually microdissected and analysed for the presence or absence of the BRAF mutation and the mutant allelic frequency using quantitative pyrosequencing. For external validation, the Cancer Genome Atlas (TCGA) data were analysed. The BRAF V600E mutation was found in 264 (82.2%) out of 321 classic PTCs in the training set. The presence of BRAF V600E was only associated with extrathyroidal extension and the absence of thyroiditis. In BRAF V600E-positive tumours, the mutant allelic frequency varied from 8 to 41% of the total BRAF alleles (median, 20%) and directly correlated with tumour size and the number of metastatic lymph nodes. Lymph node metastases were more frequent in PTCs with a high (≥20%) abundance of mutant alleles than in those with a low abundance of mutant alleles (P=0.010). These results were reinforced by validation dataset (n=348) analysis but were not reproduced in the TCGA dataset. In a population with prevalent BRAF mutations, quantitative analysis of the BRAF mutation could provide additional information regarding tumour behaviour, which is not reflected by qualitative analysis. Nonetheless, prospective studies are needed before the mutated allele percentage can be considered as a prognostic factor.

Genetic and immune divergence in pancreatic cancer lesions at the time of metastatic relapse compared to primary tumor.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4140-4140
Author(s):  
Bereket Gebregziabher ◽  
Derek A. Oldridge ◽  
Emma E. Furth ◽  
Michael D. Feldman ◽  
Andrew J. Rech ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Adjuvant Chemotherapy ◽  
Rna Sequencing ◽  
Primary Tumor ◽  
Metastatic Tumors ◽  
Kras Mutations ◽  
Primary Tumors ◽  
Metastatic Relapse ◽  
Resected Tumor ◽  
First Relapse

4140 Background: Relapse of pancreatic ductal adenocarcinoma (PDA) is common even after complete resection and adjuvant therapy. Compared to the resected tumor, the biological characteristics of metastatic tumors at the time of first relapse are poorly understood. Methods: Whole-exome sequencing (WES) (250x) and bulk RNA sequencing were performed on samples from 30 patients with PDA. Paired primary tumor samples were obtained after R0 or R1 resection, and metastatic tumor samples were obtained by biopsy at the time of first relapse. 74.1% of patients had received adjuvant chemotherapy and radiation therapy, 7.4% had received adjuvant chemotherapy only, and 3.7% had received adjuvant radiation therapy only. Most common metastatic sites were liver and lung. The cohort was 60% male with a median age at diagnosis of 64 years. The vast majority of patients had stage IIA or IIB disease at diagnosis. Median disease-free survival was 481 days. Analysis used Freebayes (somatic variant calling), Kallisto (transcript quantification), Danaher et al. (cell type deconvolution), and antigen.garnish (neoantigen prediction). Results: High-quality WES and/or RNA sequencing were available for 27/30 patients. Among these were 16 pairs of primary and metastatic samples for WES and 15 paired samples for RNA sequencing. Median tumor purity was 32% (primary) and 42% (metastatic). KRAS mutations were present in 43/48 evaluable samples, with conserved KRAS mutations in 14/16 primary-metastatic pairs. Tumors were otherwise highly variable, with 13/16 patients developing oncogenic mutations in metastatic tumors that were undetected in primary tumors (BRCA1 [3/16], AKT3 [3/16], TP53 [2/16], ROS1 [2/16]). Overall, primary and metastatic tumors had similar tumor mutation burden and neoantigen production rate. However, neoantigens were highly variable at the peptide and gene level, with conservation rates of 2.73% and 11.57%, respectively, across primary-metastatic pairs. PDA transcriptomic subtype also differed across primary-metastatic pairs in all cases. Furthermore, metastatic tumors contained lower immune suppressive signal by transcripts and deconvolution (CTLA4: p = 0.0012, FOXP3: p = 0.0026, PDCD11: p = 0.012, regulatory T cells: p = 0.012), while myeloid cells were higher (CD33: p = 0.0067). Conclusions: With the exception of KRAS, metastatic PDA tumors at relapse contain new oncogenes, distinct neoantigens, and lower immune-suppressive signal compared to primary PDA tumors. These data suggest a potential clinical utility for tumor biopsies at the time of first metastatic relapse and caution against clinical decisions for relapsed, metastatic patients based solely on sequencing of the originally resected tumor.

scholarly journals Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19

2020 ◽  
Author(s):  
Anjali Dhall ◽  
Sumeet Patiyal ◽  
Neelam Sharma ◽  
Salman Sadullah Usmani ◽  
Gajendra P S Raghava
Keyword(s):  
Scientific Community ◽  
Prediction Models ◽  
Vital Role ◽  
Machine Learning Techniques ◽  
Validation Dataset ◽  
Independent Validation ◽  
Immune Epitope ◽  
Learning Techniques ◽  
Wide Range ◽  
Immune Epitope Database

Abstract Interleukin 6 (IL-6) is a pro-inflammatory cytokine that stimulates acute phase responses, hematopoiesis and specific immune reactions. Recently, it was found that the IL-6 plays a vital role in the progression of COVID-19, which is responsible for the high mortality rate. In order to facilitate the scientific community to fight against COVID-19, we have developed a method for predicting IL-6 inducing peptides/epitopes. The models were trained and tested on experimentally validated 365 IL-6 inducing and 2991 non-inducing peptides extracted from the immune epitope database. Initially, 9149 features of each peptide were computed using Pfeature, which were reduced to 186 features using the SVC-L1 technique. These features were ranked based on their classification ability, and the top 10 features were used for developing prediction models. A wide range of machine learning techniques has been deployed to develop models. Random Forest-based model achieves a maximum AUROC of 0.84 and 0.83 on training and independent validation dataset, respectively. We have also identified IL-6 inducing peptides in different proteins of SARS-CoV-2, using our best models to design vaccine against COVID-19. A web server named as IL-6Pred and a standalone package has been developed for predicting, designing and screening of IL-6 inducing peptides (https://webs.iiitd.edu.in/raghava/il6pred/).

Relationship of Ki-67 proliferative index and metastatic tumor of breast cancer.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. e22190-e22190
Author(s):  
Kokoro Kobayashi ◽  
Yoshinori Ito ◽  
Akiko Ogiya ◽  
Naoya Gomi ◽  
Rie Horii ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Tumor ◽  
Metastatic Tumor ◽  
Labeling Index ◽  
Proliferation Index ◽  
Luminal Breast Cancer ◽  
Line Treatment ◽  
Metastatic Tumors ◽  
Ki 67 ◽  
Primary Tumors

e22190 Background: The metastatic breast tumor tends to be more aggressive with high proliferation, but this has not been proven in clinical sampling of metastatic tumors. Methods: Forty-eight patients who had histological specimens of both primary and metastatic sites of luminal breast cancer (ER and/or PgR positive and HER2 negative) were examined. We classified them as luminal A (LA) with Ki-67 labeling index of less than 14% and as luminal B (LB) with Ki-67 labeling index of more than 14%. We analyzed their overall survival (OS) and progression free survival (PFS) of 1st line treatment of each subtype of primary and metastatic tumors. Results: Subtypes of primary tumors and metastatic tumors were as follows; the primary tumor: LA; 34 patients (70.8%), LB; 14 (29.2%), metastatic tumors: LA; 21 (43.8%), LB; 27 (56.2%). Patients with LA of the primary tumor demonstrated statistically longer OS (LA; 72.5 months, LB 39.6 months, p=0.009). OS depended on the subtype of the primary tumor. In contrast, patients with LB of a metastatic tumor showed a statistically worse PFS (LA; 20.5 months, LB; 11.5 months, p=0.040). PFS of the 1st line treatment for MBC depended on the subtype of the metastatic tumor. Conclusions: The frequency of LB was increased on metastatic tumors and tended to acquire a higher proliferation index. This suggests that characterization of metastatic tumors could be better as an indicator of subsequent treatment for MBC. [Table: see text]

scholarly journals Cis-Compound Mutations are Prevalent in Triple Negative Breast Cancer and Can Drive Tumor Progression

2016 ◽  
Author(s):  
Nao Hiranuma ◽  
Jie Liu ◽  
Chaozhong Song ◽  
Jacob Goldsmith ◽  
Michael Dorschner ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Triple Negative ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Single Nucleotide Variants ◽  
Primary Tumors ◽  
Cancer Subtypes ◽  
Multiple Biopsies ◽  
Cancer Genome Atlas

About 16% of breast cancers fall into a clinically aggressive category designated triple negative (TNBC) due to a lack of ERBB2, estrogen receptor and progesterone receptor expression1-3. The mutational spectrum of TNBC has been characterized as part of The Cancer Genome Atlas (TCGA)4; however, snapshots of primary tumors cannot reveal the mechanisms by which TNBCs progress and spread. To address this limitation we initiated the Intensive Trial of OMics in Cancer (ITOMIC)-001, in which patients with metastatic TNBC undergo multiple biopsies over space and time5. Whole exome sequencing (WES) of 67 samples from 11 patients identified 426 genes containing multiple distinct single nucleotide variants (SNVs) within the same sample, instances we term Multiple SNVs affecting the Same Gene and Sample (MSSGS). We find that >90% of MSSGS result from cis-compound mutations (in which both SNVs affect the same allele), that MSSGS comprised of SNVs affecting adjacent nucleotides arise from single mutational events, and that most other MSSGS result from the sequential acquisition of SNVs. Some MSSGS drive cancer progression, as exemplified by a TNBC driven by FGFR2(S252W;Y375C). MSSGS are more prevalent in TNBC than other breast cancer subtypes and occur at higher-than-expected frequencies across TNBC samples within TCGA. MSSGS may denote genes that play as yet unrecognized roles in cancer progression.

FGFR3 protein expression and gene mutation in primary and metastatic urothelial carcinoma (UC) tumors.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 4577-4577
Author(s):  
Jonathan E. Rosenberg ◽  
Lillian Werner ◽  
Aristotelis Bamias ◽  
Toni K. Choueiri ◽  
Fabio A. B. Schutz ◽  
...  
Keyword(s):  
Protein Expression ◽  
Therapeutic Target ◽  
Primary Tumor ◽  
Scoring Systems ◽  
Metastatic Tumor ◽  
Copy Number Gain ◽  
Tissue Microarrays ◽  
Metastatic Tumors ◽  
Primary Tumors ◽  
Fgfr3 Mutation

4577 Background: FGFR3 protein expression may represent a valid therapeutic target in metastatic UC. The prevalence of both mutation and overexpression is unknown in metastatic UC. Methods: Tissue microarrays of formalin fixed paraffin-embedded urothelial carcinomas (UC) were stained for FGFR3 by immunohistochemistry (IHC) [primary (n=250); metastatic (n=31); of which (n=14) were paired]. FGFR3 immunostaining was scored as negative or positive based on previously reported scoring systems. FGFR3 mutation in primary tumors was assessed by iPlex and confirmed by hME sequencing (n=141) or Affymetrix OncoScan FFPE Express 2.0 (primary: n=17; metastases n=31). Results: FGFR3 IHC positivity was present in 48% of metastases (95% CI=32-65%) and 26% of primary tumors, (95%=CI 21-32%), though strong staining was rare (<1%). Paired primary and metastatic tumors were both negative in 50% of cases, with 14% positive only in the metastasis, 14% positive only in the primary tumor, and 21% positive in both. If the primary tumor showed staining, 71% of the metastases showed staining. FGFR3 IHC staining did not impact overall survival (p=0.8). FGFR3 mutations were observed in 9.6% of metastatic tumors (95% CI=3.3-25%), compared to 3.5% of primary tumors (95% CI=1.5%-8%). Co-occurrence of mutation and FGFR3 DNA copy number gain was observed in one specimen. Conclusions: FGFR3 IHC staining is present 26 % of primary tumors of patients who go on to develop metastatic disease, and nearly half of metastatic tumor sites. FGFR3 mutation frequency in primary and metastatic tumor specimens is low. Further investigation of the frequency of FGFR3 protein expression in metastases is needed. The presence of FGFR3 protein by IHC staining in primary and metastatic specimens suggests that FGFR3 may represent a therapeutic target even in the absence of mutation. Further functional studies are needed.

scholarly journals Gene signature characteristic of elevated stromal infiltration and activation is associated with increased risk of hematogenous and lymphatic metastasis in serous ovarian cancer

2019 ◽  
Author(s):  
Huiran Yue ◽  
Jieyu Wang ◽  
Ruifang Chen ◽  
Xiaoman Hou ◽  
Jun Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Lymphatic Metastasis ◽  
Distant Metastases ◽  
Tumor Stroma ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Primary Tumors ◽  
Tumor Invasiveness ◽  
Increased Risk

Abstract Background The clinical significance of hematogenous and lymphatic metastasis in ovarian cancer has been increasingly addressed, as it plays an imperative role in the formation of both intraperitoneal and distant metastases. Our objective is to identify the key molecules and biological processes potentially related to this relatively novel metastatic route in serous ovarian cancer.Methods Since lymphovascular space invasion (LVSI) is considered as the first step of hematogenous and lymphatic dissemination, we developed a gene signature mainly based on the transcriptome profiles with available information on LVSI status in the Cancer Genome Atlas (TCGA) dataset. We then explored the underlying biological rationale and prognostic value of the identified gene signature using multiple public databases.Results We observe that primary tumors with increased risk of hematogenous and lymphatic metastasis highly express a panel of genes, namely POSTN, LUM, THBS2, COL3A1, COL5A1, COL5A2, FAP1 and FBN1. The identified geneset is characterized by enhanced deposition of extracellular matrix and extensive stromal activation. Mechanistically, both the recruitment and the activation of stromal cells, especially fibroblasts, are closely associated with lymphovascular metastasis. Survival analysis further reveals that the elevated expression of the identified genes correlates to cancer progression and poor prognosis in patients with serous ovarian cancer.Conclusions Our findings indicate that tumor stroma supports the hematogenous and lymphatic spread of ovarian cancer, increasing tumor invasiveness and ultimately resulting in worse survival. Thus stroma-targeted therapies may improve the clinical outcomes in combination with cytoreductive surgery and chemotherapy.

scholarly journals PD-L1 expression in liver metastasis: its clinical significance and discordance with primary tumor in colorectal cancer

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xiao-Li Wei ◽  
Xuan Luo ◽  
Hui Sheng ◽  
Yun Wang ◽  
Dong-Liang Chen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Liver Metastases ◽  
Primary Tumor ◽  
Checkpoint Inhibitors ◽  
Tissue Microarrays ◽  
Tumor Differentiation ◽  
Metastatic Tumors ◽  
Primary Tumors ◽  
Expression Cluster

Abstract Background The outcomes of immune checkpoint inhibitors in cancer patients with liver metastases are poor, which may be related to a different tumor microenvironment in liver metastases from primary tumors. This study was aimed to analyze PD-L1 expression and the immune microenvironment status in liver metastases and compare the differences of PD-L1 expression between primary tumors and liver metastases of colorectal cancer. Methods 74 cases of pathologically confirmed colorectal cancer with liver metastasis underwent resection from our hospital were included. Tissue microarrays were used for the interpretation of PD-L1 expression, cluster of differentiation 4 (CD4) and CD8 density by immunohistochemistry. We evaluated the disparity between primary tumor and liver metastasis in PD-L1 expression, CD4 and CD8 density and analyzed the factors associated with obvious PD-L1 disparity. Results The expression of PD-L1 was positively related to the density of CD4 and CD8 in liver metastases. The expression of PD-L1 in liver metastases was higher than in primary tumors in certain subgroups, including patients with concurrent liver metastases (n = 63, p = 0.05), patients receiving concurrent resection of primary and metastatic tumors (n = 56, p = 0.04). The two subgroups generally reflected those without inconsistent external influences, such as treatment and temporal factors, between primary tumors and liver metastases. In these subgroups, the intrinsic differences of microenvironment between primary tumors and liver metastases could be identified. Furthermore, tumor differentiation [moderate vs. poor: OR = 0.23, 95% CI: 0.03–0.99, p = 0.05)] were demonstrated to be associated with obvious discordance of PD-L1 expression between primary tumors and liver metastases. Conclusions The expression of PD-L1 in liver metastases was higher than in primary tumors in subgroups, reflecting intrinsic microenvironment differences between primary and metastatic tumors. Obvious discordance of PD-L1 expression between primary tumor and liver metastasis was significantly related to the tumor differentiation.

scholarly journals Gene signature characteristic of elevated stromal infiltration and activation is associated with increased risk of hematogenous and lymphatic metastasis in serous ovarian cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Huiran Yue ◽  
Jieyu Wang ◽  
Ruifang Chen ◽  
Xiaoman Hou ◽  
Jun Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Progression ◽  
Lymphatic Metastasis ◽  
Distant Metastases ◽  
Tumor Stroma ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Serous Ovarian Cancer ◽  
Primary Tumors ◽  
Increased Risk

Abstract Background The clinical significance of hematogenous and lymphatic metastasis in ovarian cancer has been increasingly addressed, as it plays an imperative role in the formation of both intraperitoneal and distant metastases. Our objective is to identify the key molecules and biological processes potentially related to this relatively novel metastatic route in serous ovarian cancer. Methods Since lymphovascular space invasion (LVSI) is considered as the first step of hematogenous and lymphatic dissemination, we developed a gene signature mainly based on the transcriptome profiles with available information on LVSI status in the Cancer Genome Atlas (TCGA) dataset. We then explored the underlying biological rationale and prognostic value of the identified gene signature using multiple public databases. Results We observe that primary tumors with increased risk of hematogenous and lymphatic metastasis highly express a panel of genes, namely POSTN, LUM, THBS2, COL3A1, COL5A1, COL5A2, FAP1 and FBN1. The identified geneset is characterized by enhanced deposition of extracellular matrix and extensive stromal activation. Mechanistically, both the recruitment and the activation of stromal cells, especially fibroblasts, are closely associated with lymphovascular metastasis. Survival analysis further reveals that the elevated expression of the identified genes correlates to cancer progression and poor prognosis in patients with serous ovarian cancer. Conclusions Our findings indicate that tumor stroma supports the hematogenous and lymphatic spread of ovarian cancer, increasing tumor invasiveness and ultimately resulting in worse survival. Thus stroma-targeted therapies may improve the clinical outcomes in combination with cytoreductive surgery and chemotherapy.

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