A New Epitope Selection Method: Application to Design a Multi-Valent Epitope Vaccine Targeting HRAS Oncogene in Squamous Cell Carcinoma

We developed an epitope selection method for the design of MHC targeting peptide vaccines. The method utilizes predictions for several clinical checkpoint filters, including binding affinity, immunogenicity, antigenicity, half-life, toxicity, IFNγ release, and instability. The accuracy of the prediction tools for these filter variables was confirmed using experimental data obtained from the Immune Epitope Database (IEDB). We also developed a graphical user interface computational tool called ‘PCOptim’ to assess the success of an epitope filtration method. To validate the filtration methods, we used a large data set of experimentally determined, immunogenic SARS-CoV-2 epitopes, which were obtained from a meta-analysis. The validation process proved that placing filters on individual parameters was the most effective method to select top epitopes. For a proof-of-concept, we designed epitope-based vaccine candidates for squamous cell carcinoma, selected from the top mutated epitopes of the HRAS gene. By comparing the filtered epitopes to PCOptim’s output, we assessed the success of the epitope selection method. The top 15 mutations in squamous cell carcinoma resulted in 16 CD8 epitopes which passed the clinical checkpoints filters. Notably, the identified HRAS epitopes are the same as the clinical immunogenic HRAS epitope-based vaccine candidates identified by the previous studies. This indicates further validation of our filtration method. We expect a similar turn-around for the other designed HRAS epitopes as a vaccine candidate for squamous cell carcinoma. Furthermore, we obtained a world population coverage of 89.45% for the top MHC Class I epitopes and 98.55% population coverage in the absence of the IFNγ release clinical checkpoint filter. We also identified some of the predicted human epitopes to be strong binders to murine MHC molecules, which provides insight into studying their immunogenicity in preclinical models. Further investigation in murine models could warrant the application of these epitopes for treatment or prevention of squamous cell carcinoma.

Download Full-text

Epithelioid Trophoblastic Tumor: An Outcome-Based Literature Review of 78 Reported Cases

International Journal of Gynecological Cancer ◽

10.1097/igc.0b013e31829ea023 ◽

2013 ◽

Vol 23 (7) ◽

pp. 1334-1338 ◽

Cited By ~ 26

Author(s):

Xiaofei Zhang ◽

Weiguo Lü ◽

Bingjian Lü

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Figo Stage ◽

Lower Uterine Segment ◽

Reproductive Age ◽

Small Data ◽

Data Set ◽

Trophoblastic Tumor ◽

Epithelioid Trophoblastic Tumor

ObjectivesEpithelioid trophoblastic tumor (ETT) is very rare; and therefore, a substantially increased data set is unlikely to be obtained in the near future. This analysis aimed to assess the effects of current management on clinical outcomes and to identify potential prognostic indicators in ETT.MethodsWe applied a literature search using PubMed to analyze the clinical data of 78 published cases of ETT.ResultsWomen with ETT present at reproductive age (mean ± SD, 37.1 ± 8.7 years) and have a slightly to moderately elevated serum β-human chorionic gonadotropin (median, 665 IU/L). Epithelioid trophoblastic tumor is frequently present in the lower uterine segment/cervix (26/58 cases) and can be misdiagnosed as squamous cell carcinoma (6/26). Lung is the most common extrauterine site of ETT (5/11 with uterine ETT and 10/20 without uterine ETT). Kaplan-Meier analysis indicates that chemotherapy (surgery with postoperative chemotherapy vs surgery alone) is associated with increased ETT relapse (P= 0.005), even after stratification by International Federation of Gynecology and Obstetrics (FIGO) stage (P= 0.008); but FIGO stage remains the only significant prognostic indicator for ETT (P= 0.015).ConclusionsThis analysis confirms the hypothetical chemotherapy resistance and prognostic value of FIGO staging in ETT. These findings remain tentative given the small data set available for analysis and the reporting bias from these published cases; however, they may confer a risk-adapted therapy. Finally, both gynecologists and pathologists should be alert to the potential misdiagnosis of squamous cell carcinoma when ETT is present in the lower uterine segment/cervix.

Download Full-text

Malignant Proliferating Pilar Tumor: A Rare Mimic of Squamous Cell Carcinoma

American Journal of Clinical Pathology ◽

10.1093/ajcp/aqaa161.073 ◽

2020 ◽

Vol 154 (Supplement_1) ◽

pp. S35-S36

Author(s):

W Beversdorf ◽

E Rinker

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Neck Mass ◽

Pathology Report ◽

Small Data ◽

Ki 67 ◽

Data Set ◽

Tumor Group ◽

Pathologic Features

Abstract Introduction/Objective Proliferating pilar tumor is a rare cutaneous adnexal neoplasm, closely resembling and potentially misdiagnosed as conventional squamous cell carcinoma. Malignant forms are recognized; however, differentiating criteria have not been firmly established due to their exceptional rarity. Prognosis is variable, with recurrence or metastasis reported in up to 25% of patients within a very small data set. Methods We present a case of a 31 year old male who underwent excision of a posterior neck mass clinically presumed to be a recurrent benign cyst in 2018. Initial excision was performed at an outside institution approximately 10 years prior, and a pathology report was not included in his record. Results Our resection specimen contained a 5.5 cm lobulated, cystic and solid mass involving the dermis and subcutis with superficial ulceration. Tumor histology was consistent with malignant proliferating pilar tumor as described in other reported cases, showing a proliferation of pleomorphic squamous cells infiltrating the dermis and associated desmoplasia. The tumor featured abundant pilar keratinization with focal necrosis and increased mitotic activity. Numerous smaller pilar cysts exhibiting varying degrees of squamous atypia studded the periphery of the dominant mass. The immunohistochemical profile of this case also exhibited similarities to other reports, with focal positivity for calretinin and CD34 as well as an increased Ki-67 proliferative index (up to 70–80%). While other reports document diffuse expression of p53, our case demonstrated complete absence of p53 staining. Conclusion We present this case to highlight the importance of recognizing pilar differentiation within squamous lesions, examine pathologic features associated with malignant behavior, and discuss the relationship between histologic characteristics and clinical outcomes in this exceedingly rare tumor group.

Download Full-text

The Histopathological Diagnosis of Adenocarcinoma & Squamous Cells Carcinoma of Lungs by Artificial intelligence: A comparative study of convolutional neural networks

10.1101/2020.05.02.20044602 ◽

2020 ◽

Author(s):

Mohammad Ali Abbas ◽

Syed Usama Khalid Bukhari ◽

Asmara Syed ◽

Syed Sajid Hussain Shah

Keyword(s):

Lung Cancer ◽

Neural Networks ◽

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Convolutional Neural Networks ◽

Squamous Cell ◽

Digital Pathology ◽

Histopathological Diagnosis ◽

Data Set ◽

Diagnosis Of Lung Cancer

AbstractIntroductionMalignant tumors of the lung are the most important cause of morbidity and mortality due to cancer all over the world. A rising trend in the incidence of lung cancer has been observed. Histopathological diagnosis of lung cancer is a vital component of patient care. The use of artificial intelligence in the histopathological diagnosis of lung cancer may be a very useful technology in the near future.AimThe aim of the present research project is to determine the effectiveness of convolutional neural networks for the diagnosis of squamous cell carcinoma and adenocarcinoma of the lung by evaluating the digital pathology images of these cancers.Materials & MethodsA total of 15000 digital images of histopathological slides were acquired from the LC2500 dataset. The digital pathology images from lungs are comprised of three classes; class I contains 5000 images of benign lung tissue, class II contains 5,000 images of squamous cell carcinoma of lungs while Class III contains 5,000 images of adenocarcinoma of lungs. Six state of the art off the shelf convolutional neural network architectures, VGG-19, Alex Net, ResNet: ResNet-18, ResNet-34, ResNet-50, and ResNet-101, are used to assess the data, in this comparison study. The dataset was divided into a train set, 55% of the entire data, validation set 20%, and 25% into the test data set.ResultsA number of off the shelf pre-trained (on ImageNet data set) convolutional neural networks are used to classify the histopathological slides into three classes, benign lung tissue, squamous cell carcinoma-lung and adenocarcinoma - lung. The F-1 scores of AlexNet, VGG-19, ResNet-18, ResNet-34, ResNet-50 and ResNet-101, on the test dataset show the result of 0.973, 0.997, 0.986, 0.992, 0.999 and 0.999 respectively.DiscussionThe diagnostic accuracy of more 97% has been achieved for the diagnosis of squamous cell carcinoma and adenocarcinoma of the lungs in the present study. A similar finding has been reported in other studies for the diagnosis of metastasis of breast carcinoma in lymph nodes, basal cell carcinoma, and prostatic cancer.ConclusionThe development of algorithms for the recognition of a specific pattern of the particular malignant tumor by analyzing the digital images will reduce the chance of human errors and improve the efficiency of the laboratory for the rapid and accurate diagnosis of cancer.

Download Full-text

A Novel Immune-Related Seventeen-Gene Signature for Predicting Early Stage Lung Squamous Cell Carcinoma Prognosis

Frontiers in Immunology ◽

10.3389/fimmu.2021.665407 ◽

2021 ◽

Vol 12 ◽

Author(s):

Tao Fan ◽

Zhiliang Lu ◽

Yu Liu ◽

Liyu Wang ◽

He Tian ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Predictive Value ◽

Early Stage ◽

Lung Squamous Cell Carcinoma ◽

Gene Signature ◽

Related Gene ◽

Data Set ◽

Immune Related Gene

With the increasingly early stage lung squamous cell carcinoma (LUSC) being discovered, there is an urgent need for a comprehensive analysis of the prognostic characteristics of early stage LUSC. Here, we developed an immune-related gene signature for outcome prediction of early stage LUSC based on three independent cohorts. Differentially expressed genes (DEGs) were identified using CIBERSORT and ESTMATE algorithm. Then, a 17-immune-related gene (RPRM, APOH, SSX1, MSGN1, HPR, ISM2, FGA, LBP, HAS1, CSF2, RETN, CCL2, CCL21, MMP19, PTGIS, F13A1, C1QTNF1) signature was identified using univariate Cox regression, LASSO regression and stepwise multivariable Cox analysis based on the verified DEGs from 401 cases in The Cancer Genome Atlas (TCGA) database. Subsequently, a cohort of GSE74777 containing 107 cases downloaded from Gene Expression Omnibus (GEO) database and an independent data set consisting of 36 frozen tissues collected from National Cancer Center were used to validate the predictive value of the signature. Seventeen immune-related genes were identified from TCGA cohort, which were further used to establish a classification system to construct cases into high- and low-risk groups in terms of overall survival. This classifier was still an independent prognostic factor in multivariate analysis. In addition, another two independent cohorts and different clinical subgroups validated the significant predictive value of the signature. Further mechanism research found early stage LUSC patients with high risk had special immune cell infiltration characteristics and gene mutation profiles. In conclusion, we characterized the tumor microenvironment and established a highly predictive model for evaluating the prognosis of early stage LUSC, which may provide a lead for effective immunotherapeutic options tailored for each subtype.

Download Full-text

Identification and validation of a novel drug target in an organoid model of esophageal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.4_suppl.46 ◽

2018 ◽

Vol 36 (4_suppl) ◽

pp. 46-46

Author(s):

Navika Shukla ◽

Ameen Abdulla Salahudeen ◽

Sean de la O ◽

Daniel James Hart ◽

Gregory Taylor ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Copy Number ◽

Cell Cancer ◽

Functional Screening ◽

Data Set ◽

Immunodeficient Mice

46 Background: Esophageal squamous cell carcinomas remains a particularly intractable disease due to limited therapeutic options as well as a lack of targeted therapies. The genetic landscape of esophageal squamous cell carcinoma is varied, but a common means of tumorigenesis in squamous cancers are alterations in copy number of putative oncogenic loci that result in upregulated mRNA. Within this subset of loci with copy number alterations, however, it has been difficult to distinguish between driver and passenger mutations using traditional in vitro models. Methods: We functionally screened a data set of amplified “outlier” candidates nominated through a bioinformatics pipeline that scored chromosomal amplifications with linked mRNA overexpression. Screening and validation was performed in a novel three-dimensional organoid model of esophageal squamous cell carcinoma that served as a tabula rasa by virtue of a single p53 null alteration. Results: Functional screening uncovered a novel oncogenic mechanism that serves to drive esophageal squamous cell cancer tumorigenesis both in vitro and in vivo when subcutaneously transplanted into immunodeficient mice. In addition, pharmacologic perturbation of this mechanism resulted in attenuation of the oncogenic phenotype in vitro. Conclusions: We have paired bioinformatics analysis of TCGA data with a p53 null organoid model to functionally validate a novel driver mechanism of esophageal squamous cell carcinoma. Studies are underway to translate these findings and hopefully generate additional therapeutic strategies for esophageal squamous cell carcinoma patients.

Download Full-text

A 16-gene signature predicting prognosis of patients with oral tongue squamous cell carcinoma

PeerJ ◽

10.7717/peerj.4062 ◽

2017 ◽

Vol 5 ◽

pp. e4062 ◽

Cited By ~ 12

Author(s):

Zeting Qiu ◽

Wei Sun ◽

Shaowei Gao ◽

Huaqiang Zhou ◽

Wulin Tan ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Survival Analysis ◽

Cell Carcinoma ◽

Risk Score ◽

Squamous Cell ◽

Gene Signature ◽

Integrated Analysis ◽

Data Sets ◽

Oral Tongue ◽

Data Set

Background Oral tongue squamous cell carcinoma (OTSCC) is the most common subtype of oral cancer. A predictive gene signature is necessary for prognosis of OTSCC. Methods Five microarray data sets of OTSCC from the Gene Expression Omnibus (GEO) and one data set from The Cancer Genome Atlas (TCGA) were obtained. Differentially expressed genes (DEGs) of GEO data sets were identified by integrated analysis. The DEGs associated with prognosis were screened in the TCGA data set by univariate survival analysis to obtain a gene signature. A risk score was calculated as the summation of weighted expression levels with coefficients by Cox analysis. The signature was used to distinguish carcinoma, estimated by receiver operator characteristic curves and the area under the curve (AUC). All were validated in the GEO and TCGA data sets. Results Integrated analysis of GEO data sets revealed 300 DEGs. A 16-gene signature and a risk score were developed after survival analysis. The risk score was effective to stratify patients into high-risk and low-risk groups in the TCGA data set (P < 0.001). The 16-gene signature was valid to distinguish the carcinoma from normal samples (AUC 0.872, P < 0.001). Discussion We identified a useful 16-gene signature for prognosis of OTSCC patients, which could be applied to clinical practice. Further studies were needed to prove the findings.

Download Full-text

Incidence of nasopharyngeal carcinoma in Belgrade during the period 1991-2005

Vojnosanitetski pregled ◽

10.2298/vsp0906473n ◽

2009 ◽

Vol 66 (6) ◽

pp. 473-476 ◽

Cited By ~ 3

Author(s):

Vladimir Nesic ◽

Sandra Sipetic ◽

Hristina Vlajinac ◽

Dragan Miljus ◽

Svetlana Stosic-Divjak ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Nasopharyngeal Carcinoma ◽

Cell Carcinoma ◽

Incidence Rate ◽

Squamous Cell ◽

Direct Method ◽

Undifferentiated Carcinoma ◽

Incidence Rates ◽

Capital City ◽

World Population

Background/Aim. Nasopharyngeal carcinoma (NPC) is a relatively rare malignant disease, of which 80 000 individuals become ill around the world annually, which amounts to 0.7% of all carcinomas. The aim of this descriptive study was to analyze NPC incidence in Belgrade (the capital city of Serbia, with about 1.6 million inhabitants) during the period 1991-2005. Methods. In data analysis, crude rates age and sex specific rates, and standardized incidence rates were used. Standardization was performed by a direct method, using world population as the standard. Results. In Belgrade, during the observed 15-year-period, the number of new NPC patients totaled 118, of which 86 (72.9%) were male and 32 (27.1%) were female. The average standardized incidence rate for men was 0.52 per 100 000 and for women 0.16 per 100 000. In both sexes the incidence was very low before 40 years of age. In men, the greatest incidence rate of NPC was in the 50-59 years age group, and in women in those 60 and more years old. Furthermore, undifferentiated carcinoma of nasopharyngeal type was 3.6 times more often in comparison to squamous cell carcinoma. Conclusion. Belgrade belongs to a region with a low incidence rate of NPC. Further investigations are needed to explain higher frequency of undifferentiated carcinoma of nasopharyngeal type than squamous cell carcinoma.

Download Full-text

Nomogram based on SIS predicting the survival of non-surgical thoracic esophageal squamous cell carcinoma treated by IMRT

10.21203/rs.3.rs-404753/v1 ◽

2021 ◽

Author(s):

Xingyu Du ◽

Shuchai Zhu ◽

Jing Dong ◽

Ke Yan ◽

Xiaobin Wang ◽

...

Keyword(s):

Overall Survival ◽

Squamous Cell Carcinoma ◽

Prognostic Factors ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Inflammatory Markers ◽

Progression Free Survival ◽

Data Set ◽

Free Survival

Abstract Background: Several inflammatory markers have been reported to be associated with clinical outcomes in patients with esophageal squamous cell carcinoma (ESCC). This study was to evaluate several pre-radiotherapy serum inflammatory indicators, including the neutrophil / lymphocytes ratio (NLR), platelet / lymphocyte (PLR), systemic immune-inflammatory index (SII), systemic inflammation score(SIS), and compare which one has the highest predicted survival value. Finally, combining inflammatory markers with traditional prognostic factors, a new Nomogram model was developed to predict overall survival (OS) and progression-free survival (PFS) for ESCC patients receiving radiotherapy (RT) or chemoradiotherapy (CRT). Methods: This study retrospectively reviewed the data of 245 patients with thoracic esophageal squamous cell carcinoma (ESCC) underwent RT or CRT in the Fourth Hospital of Hebei Medical University from January 2013 to December 2015. The survival differences of these indexes were compared by the Kaplan-Meier method, and the univariate and the multivariate analyses were performed to determine these prognostic factors of overall survival (OS) and progression-free survival (PFS). Multivariate Cox proportional hazards regression models were used to create nomogram for OS and PFS.Results: 239 patients met the eligibility criteria. The estimated 1-, 3-, and 5-year OS and PFS rates were 74.6%, 36.8%, 26.5% and 58.4%, 31.3%, 20.5%, respectively, for the whole group. The difference in survival between OS and PFS was significant when univariate analysis were applied based on these inflammation-based measures. Multivariate analysis showed that tumor length, T stage, TNM stage, chemotherapy, SIS were predictive variables for OS and PFS in the multivariate model. The nomogram model established based on multivariate models of training data set had good predictive ability, the unadjusted C-index was 0.701 (95% CI, 0.662– 0.740) and 0.695 (95% CI, 0.656 - 0.734) for OS and PFS. Conclusions: This study show that SIS, as a comprehensive indicator of inflammation and nutrition, had the strongest predictive power for evaluating prognosis. Moreover, our nomogram can accurately predict OS and PFS after treatment and may provide guidance regarding adjuvant therapy and surveillance.

Download Full-text

STAT3 decoy oligonucleotide-carrying microbubbles with pulsed ultrasound for enhanced therapeutic effect in head and neck tumors

PLoS ONE ◽

10.1371/journal.pone.0242264 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0242264

Author(s):

Thiruganesh Ramasamy ◽

Xucai Chen ◽

Bin Qin ◽

Daniel E. Johnson ◽

Jennifer R. Grandis ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Tumor Progression ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Clinical Translation ◽

Data Set ◽

Decoy Oligonucleotide ◽

Stat3 Decoy

Signal transducer and activator of transcription-3 (STAT3) is an oncogenic transcription factor implicated in carcinogenesis, tumor progression, and drug resistance in head and neck squamous cell carcinoma (HNSCC). A decoy oligonucleotide targeting STAT3 offers a promising anti-tumor strategy, but achieving targeted tumor delivery of the decoy with systemic administration poses a significant challenge. We previously showed the potential for STAT3 decoy-loaded microbubbles, in conjunction with ultrasound targeted microbubble cavitation (UTMC), to decrease tumor growth in murine squamous cell carcinoma. As a next step towards clinical translation, we sought to determine the anti-tumor efficacy of our STAT3 decoy delivery platform against human HNSCC and the effect of higher STAT3 decoy microbubble loading on tumor cell inhibition. STAT3 decoy was loaded on cationic lipid microbubbles (STAT3-MB) or loaded on liposome-conjugated lipid microbubbles to form STAT3-loaded liposome-microbubble complexes (STAT3-LPX). UTMC treatment efficacy with these two formulations was evaluated in vitro using viability and apoptosis assays in CAL33 (human HNSCC) cells. Anti-cancer efficacy in vivo was performed in a CAL33 tumor murine xenograft model. UTMC with STAT3-MB caused significantly lower CAL33 cell viability compared to UTMC with STAT3-LPX (56.8±8.4% vs 84.5±8.8%, respectively, p<0.05). In vivo, UTMC with STAT3-MB had strong anti-tumor effects, with significantly less tumor burden and greater survival compared to that of UTMC with microbubbles loaded with a mutant control decoy and untreated control groups (p<0.05). UTMC with STAT3 decoy-loaded microbubbles significantly decreases human HNSSC tumor progression. These data set the stage for clinical translation of our microbubble platform as an imaged-guided, targeted delivery strategy for STAT3 decoy, or other nucleotide-based therapeutics, in human cancer treatment.

Download Full-text