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1.
J Cancer Res Ther ; 19(Suppl 2): S712-S718, 2023 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-38384044

RESUMO

BACKGROUND AND OBJECTIVES: Epidermal growth factor receptor (EGFR) mutation analysis has become an important part of the initial workup of non-squamous non-small cell lung cancer (NS-NSCLC) patients. This study is attempted as South Indians population is comprised of ethnic groups with diverse genetic makeup and only very limited data on EGFR mutation is available from south India. A detailed understanding of EGFR mutation profile will help in better planning of treatment strategies and resource allocation. METHODS: A retrospective analysis of EGFR mutation frequency in 350 patients diagnosed with adenocarcinoma of lung and its association with pathological characteristics was done. RESULTS: Out of 350 cases of pulmonary adenocarcinoma, within an age group ranging from 30 to 86 years. EGFR mutations were identified in 34.8% (n = 122) cases, out of which 35.24% (n = 43) were in non-smoker females (P = 0.001). Of the 14 cases with resistant type of EGFR mutations, nine were in smoker males and the remaining five in non-smoker females. INTERPRETATION AND CONCLUSION: Overall EGFR mutation frequency observed in our study was similar to other Indian studies. However, in our study, we observed that mutation in exon 21 was less frequent compared to other studies. A similar slightly increased frequency of rare mutations and double mutations were observed in our study. A detailed study of the molecular epidemiology of lung cancer and its association with different geographical zones of India is needed. This understanding will help in better planning of treatment strategies and resource allocation.


Assuntos
Adenocarcinoma de Pulmão , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Masculino , Feminino , Humanos , Adulto , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Estudos Retrospectivos , Receptores ErbB/genética , Adenocarcinoma de Pulmão/genética , Índia/epidemiologia , Mutação
2.
J Oral Maxillofac Pathol ; 23(1): 82-89, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31110422

RESUMO

BACKGROUND: Loco-regional recurrence is one of the major reasons for poor prognosis of oral squamous cell carcinoma (OSCC). However, till date, no feasible molecular marker is available to predict the risk of recurrence in OSCC patients. AIM: To evaluate the cell cycle regulatory genes expression and its association with the risk of recurrence in oral cancer patients. MATERIALS AND METHODS: Transcript level expressions of 47 cell cycle regulatory genes were analyzed in 73 OSCC tumors from buccal mucosa and tongue, 26 adjacent normal samples using real-time polymerase chain reaction. TaqMan low-density array data were analyzed using the DataAssist™ v 3.01. Significantly altered genes within the tumor samples and samples showing recurrence (re-appearance of disease during the follow-up in cases having complete response to initial treatment assessed after 3 months of the treatment) were identified. Further, Kyoto Encyclopedia of Genes and Genomes pathway analysis and The Cancer Genome Atlas (TCGA) online data analysis portal were used to analyze interacting protein and pathways significantly associated with the altered gene. RESULTS: CCNA1, CCNB2, CCND2, CCNE1, CCNF, CDC2, CDK6, CHEK1, and TGFA found to significantly alter in the tumor sample of oral cancer patients, and down-expression of CDKN2A and CDKN2B found to associate with the recurrence of disease in oral cancer patients. TCGA data also showed the loss of CDKN2A and CDKN2B significantly associated with recurrence in head and neck cancer patients. CONCLUSION: CDKN2A and CDKN2B expression analysis can be used as the prognostic marker for the oral cancer patients. The present method of data analysis helps overcome the limitations and complications of high throughput techniques and thereby increases the opportunity of employing molecular markers in routine clinical management of OSCC.

3.
J Cancer Res Ther ; 14(2): 403-408, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29516928

RESUMO

BACKGROUND: Our previous study showed that overexpression of cyclin D1 protein is associated with poor prognosis in oral squamous cell carcinoma (OSCC) patients. Regarding the alteration in the transactivating pathway regulating cyclin D1 expression is still unclear in OSCC from our population. OBJECTIVES: The major objective of this study is to understand the alteration associated with the transactivation pathway regulating the cyclin D1 overexpression in OSCC patients from our population. MATERIALS AND METHODS: Alteration in the transactivation pathway regulating cyclin D1 expression was evaluated in tumor sample from OSCC patients. The findings were further validated using in vitro knockdown model in OSCC cell line. RESULTS: Results from the patients' samples showed that the Phospho-STAT3 has a significant association with cyclin D1 overexpression in OSCC tumor samples. Further knockdown in vitro studies using SCC66 showed a significant correlation between STAT3 and cyclin D1 in OSCC. CONCLUSION: The results from this study showed that in our population the cyclin D1 overexpression is associated with hyperactivation of STAT3 pathway. Our previous result has shown that the cyclin D1 protein overexpression is associated with poor prognosis in OSCC patients. Hence, STAT3 pathway will be better target for the patients with increased cyclin D1 in OSCC patients from our population.


Assuntos
Carcinoma/genética , Carcinoma/metabolismo , Ciclina D1/genética , Expressão Gênica , Neoplasias Bucais/genética , Neoplasias Bucais/metabolismo , Fator de Transcrição STAT3/metabolismo , Biomarcadores Tumorais , Carcinoma/patologia , Linhagem Celular Tumoral , Ciclina D1/metabolismo , Técnicas de Silenciamento de Genes , Humanos , Imuno-Histoquímica , Índia , Neoplasias Bucais/patologia , Mutação , Proteólise , RNA Mensageiro , Fator de Transcrição STAT3/genética , Transdução de Sinais
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