Second primary cancers in laryngeal cancer patients

Occurrence of metachronous second primary cancer in head and neck cancer survivors: A systematic review and meta-analysis of the literature

OBJECTIVE

Head and neck cancer (HNC) is the sixth leading cancer worldwide with approximately 600,000 new cases per year. Several studies suggest that HNC survivors may have an increased risk of developing second primary cancers (SPCs). A systematic review and meta-analysis was performed aiming to quantify the overall and site-specific risk of metachronous SPCs in HNC survivors.

METHODS

PubMed, Web of Science and Scopus were searched to identify studies published until October 2019. Studies investigating the standardised incidence ratio (SIR) of metachronous SPC were included. A random-effects meta-analysis was performed to calculate the overall and site-specific SIRs. Newcastle-Ottawa Scale was used to assess the study's quality. Heterogeneity was quantified using the I² statistics and explored using meta-regression.

RESULTS

Twenty-six studies were included in the systematic review. Studies differed by the definition of metachronous SPC used. For the meta-analyses, the studies were grouped according to these definitions. In the three groups, the overall risk of metachronous SPC was increased. The highest SPC risk was for oropharynx, oesophagus and lung.

CONCLUSIONS

Head and neck cancer survivors are at increased overall risk of metachronous SPCs. The canonical upper aerodigestive sites, HNLE (head and neck, oesophagus and lung), were the SPC sites with the highest risk.

IMPLICATION FOR CANCER SURVIVORS

Our results emphasise the importance of targeted surveillance strategies aimed at early detection and tertiary preventive interventions.

Prognostic validation of the updated 8th edition Tumor-Node-Metastasis classification by the Union for International Cancer Control: Survival analyses of 307 patients with surgically treated gallbladder carcinoma

In December 2016, the Union for International Cancer Control (UICC) published the 8th edition of the Tumor-Node-Metastasis (TNM) classification of malignant tumors, including a number of vital changes in the definitions of the T2 category, the N category and the stages of gallbladder cancer (GBC). The clinical value of this newly updated classification in patients with surgically treated GBC has not been rigorously validated. The present study aimed to analyze the prognosis of patients with GBC in a high-volume surgical unit, and to validate the prognostic value of the new UICC TNM classification, particularly the main changes in the stages of GBC. Data from 307 patients who were surgically treated and histopathologically diagnosed with GBC between January 2011 and July 2016 in The West China Hospital (Chengdu, Sichuan, China) were retrospectively collected and analyzed. The new UICC criteria distributed 32, 60, 99 and 116 eligible patients in stages I, II, III and IV, respectively. The differences in overall survival time between each stage (I–IV) demonstrated statistical significance (P<0.05). As a result of the main change of this classification, the novel definitions of T2a and T2b effectively stratified the prognosis of patients with T2 GBC (P<0.001). Furthermore, patients with stage IIa tumors also obtained significantly improved overall survival time compared with patients with stage IIb tumors (P=0.04), whereas the comparison between patients with stage IIb and IIIa tumors did not present any notable difference (P=0.20). Additionally, the new N category stratified the survival of the patients effectively (P<0.001). Together with curative resection, this latest classification was indicated to be an independent predictor of survival via multivariate analysis (hazard ratio, 6.25; 95% confidence interval, 3.81–10.26; P<0.001). In conclusion, the newly updated UICC TNM classification could effectively reflect the clinical outcome of patients with surgically treated GBC. Furthermore, tumor location could predict the survival of surgically treated T2 GBC. The novel classification of the N category by the number of lymph nodes involved was also demonstrated to be valid.

Immunohistochemical pattern analysis of squamous cell carcinoma: Lung primary and metastatic tumors of head and neck

OBJECTIVES

This study aimed to develop an immunohistochemical (IHC) diagnostic algorithm for primary lung squamous cell carcinoma (LSCC) and pulmonary metastasis of head and neck SCC (HNSCC).

MATERIALS AND METHODS

We selected three antibodies (CK19, MMP3, and PI3) from a web-based gene expression database and an IHC analysis available online. We developed an IHC diagnostic algorithm using tissue microarrays from 39 LSCCs and 48 HNSCCs as the training set. It was validated using whole tumor sections of 32 LSCCs and 23 HNSCCs. The algorithm was applied to 28 cases with a history of HNSCC and who underwent resection of pulmonary squamous cell tumors.

RESULTS

The sensitivity, specificity, and accuracy of the algorithm were 90%, 62%, and 77%, respectively, in the training set and 96%, 44%, and 65%, respectively, in the validation set. Twenty-three of 28 SCCs were diagnosed as metastasis of HNSCC; the remaining five tumors were diagnosed as LSCC. Among the patients in the HNSCC group, 18 developed postoperative recurrence and 11 died of the disease, whereas only one patient in the LSCC group had recurrence. Compared with the LSCC group, the HNSCC group had poorer prognosis (P=0.07). IHC diagnosis coincided with the retrospective diagnosis in 22 (79%) of the 28 patients (sensitivity, 95%; specificity, 44%).

CONCLUSION

The IHC diagnostic algorithm may be clinically useful for distinguishing between LSCC and pulmonary metastasis of HNSCC.

Differential diagnosis between primary lung squamous cell carcinoma and pulmonary metastasis of head and neck squamous cell carcinoma

Differentiation between lung squamous cell carcinoma and pulmonary metastasis of head and neck squamous cell carcinoma is clinically important because the prognoses and therapeutic options are considerably different. However, the clinical, pathological, and immunohistochemical diagnostic methods have not yet been fully established. Although various molecular methods have been developed, they have not yet been practically applied. A combined approach involving molecular and immunohistochemical analysis, such as one that uses antibodies selected on the basis of comprehensive genetic analysis results, may be effective. We suggest a new diagnostic criteria using the clinical characteristics and the result of immunohistochemical analysis. However, there are two underlying problems in the development of new diagnostic methods: tumor heterogeneity and determination of the diagnostic accuracy.

Clinical parameters predicting development of pulmonary malignancies in patients treated for head and neck squamous cell carcinoma

BACKGROUND

As the locoregional control rates in head and neck squamous cell carcinoma (HNSCC) have increased, these patients may suffer distant metastasis in a higher proportion of cases. Clinicopathological characteristics allowing prediction of high-risk profile would allow adapting posttreatment surveillance to individual risk.

METHODS

A retrospective review of all patients with HNSCC treated at the Jewish General Hospital, McGill University, Montreal, Quebec, Canada, between 1999 and 2008 was conducted for this study.

RESULTS

The study included 428 patients with a mean follow-up of 65 months (±SEM 1.7). Eighty patients (18.6%) developed pulmonary malignancy during follow-up. In multivariate Cox-regression analysis, locoregional failure and current smoking were associated with higher risk of pulmonary malignancy (p < .001 and p = .008, respectively).

CONCLUSION

Locoregional failure and smoking persistence are predictors of pulmonary malignancy in patients with HNSCC. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1277-E1280, 2016.

A gene expression profile test to resolve head & neck squamous versus lung squamous cancers

Background

The differential diagnosis between metastatic head & neck squamous cell carcinomas (HNSCC) and lung squamous cell carcinomas (lung SCC) is often unresolved because the histologic appearance of these two tumor types is similar. We have developed and validated a gene expression profile test (GEP-HN-LS) that distinguishes HNSCC and lung SCC in formalin-fixed, paraffin-embedded (FFPE) specimens using a 2160–gene classification model.

Methods

The test was validated in a blinded study using a pre-specified algorithm and microarray data files for 76 metastatic or poorly-differentiated primary tumors with a known HNSCC or lung SCC diagnosis.

Results

The study met the primary Bayesian statistical endpoint for acceptance. Measures of test performance include overall agreement with the known diagnosis of 82.9% (95% CI, 72.5% to 90.6%), an area under the ROC curve (AUC) of 0.91 and a diagnostics odds ratio (DOR) of 23.6. HNSCC (N = 38) gave an agreement with the known diagnosis of 81.6% and lung SCC (N = 38) gave an agreement of 84.2%. Reproducibility in test results between three laboratories had a concordance of 91.7%.

Conclusion

GEP-HN-LS can aid in resolving the important differential diagnosis between HNSCC and lung SCC tumors.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1753227817890930

Prediagnosis smoking, obesity, insulin resistance, and second primary cancer risk in male cancer survivors: National Health Insurance Corporation Study

PURPOSE

Smoking, obesity, and insulin resistance are well-known risk factors for cancer, yet few epidemiology studies evaluate their role as risk factors for a second primary cancer (SPC).

PATIENTS AND METHODS

We identified 14,181 men with a first cancer from the National Health Insurance Corporation Study cohort. We obtained data on fasting glucose level, body mass index (BMI), and smoking history from an enrollment interview (1996). We obtained SPC incidence data for 1996 through 2002 from the Korean Central Cancer Registry. We used the standard Poisson regression model to estimate the age- and multivariate-adjusted relative risk (RR) for SPCs in relation to smoking history, BMI, and insulin resistance before diagnosis.

RESULTS

We observed 204 patients with SPC. The overall age-standardized incidence rate of SPC was 603.2 occurrences per 100,000 person-years, which was about 2.3 times higher than that of first cancer in the general male population. Multivariate regression revealed that lung (RR, 3.69; 95% CI, 1.35 to 10.09) and smoking-related (RR, 2.02; 95% CI, 1.02 to 4.03) SPCs were significantly associated with smoking. Obese patients (BMI > or = 25 kg/m2) had significantly elevated RRs for colorectal (RR, 3.45; 95% CI, 1.50 to 7.93) and genitourinary (RR, 3.61; 95% CI, 1.36 to 9.54) SPCs. Patients with a fasting serum glucose concentration > or = 126 mg/dL had a higher RR for hepatopancreatobiliary (RR, 3.33; 95% CI, 1.33 to 8.37) and smoking-related (1.93; 95% CI, 1.01 to 3.68) SPCs.

CONCLUSION

Prediagnosis smoking history, obesity, and insulin resistance were risk factors for several SPCs. These findings suggest that more thorough surveillance and screening for SPCs is needed for the cancer survivors with these risk factors.

Gene expression profiling allows distinction between primary and metastatic squamous cell carcinomas in the lung

Lung neoplasms commonly develop in patients previously treated for head and neck carcinomas. The derivation of these tumors, either as new primary lung cancers or as metastatic head and neck cancers, is difficult to establish based on clinical or histopathologic criteria since both are squamous cell carcinomas and have identical features under light microscopy. However, this distinction has significant treatment and prognostic implications. Gene expression profiling was performed on a panel of 52 sequentially collected patients with either primary lung (n = 21) or primary head and neck (n = 31) carcinomas using the Affymetrix HG_U95Av2 high-density oligonucleotide microarray. Unsupervised hierarchical clustering with Ward linkage and the Pearson correlation metric was performed. To assess robustness, bootstrap resampling was performed with 1,000 iterations. A t test of the normalized values for each gene was used to determine the genes responsible for segregating head and neck from lung primary carcinomas, and those with the most differential expression were used for later analyses. In the absence of a large "test" set of tumors, we used a supervised leave-one-out cross-validation to test how well we could predict the tumor origin. Once a gene expression profile was established, 12 lung lesions taken from patients with previously treated head and neck cancers were similarly analyzed by gene expression profiling to determine their sites of origin. Unsupervised clustering analysis separated the study cohort into two distinct groups which reliably remained segregated with bootstrap resampling. Group 1 consisted of 30 tongue carcinomas. Group 2 consisted of 21 lung cancers and 1 tongue carcinoma. The clustering was not changed even when normal lung or tongue profiles were subtracted from the corresponding carcinomatous lesions, and a leave-one-out cross-validation showed a 98% correct prediction (see Supplementary Data 1). A minimum set of 500 genes required to distinguish these groups was established. Given the ability to segregate these lesions using molecular profiling, we analyzed the lung tumors of undetermined origin. All cases clearly clustered with either lung or tongue tumor subsets, strongly supporting our hypothesis that this technique could elucidate the tissue of origin of metastatic lesions. Although histologically similar, squamous cell carcinomas have distinct gene expression profiles based on their anatomic sites of origin. Accordingly, the application of gene expression profiling may be useful in identifying the derivation of lung nodules and consequently enhances treatment planning.