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Tissue inhibitor of metalloproteinase-1 (TIMP-1) is an important regulator of extracellular matrix turnover that has been traditionally regarded as a potential tumor suppressor owing to its inhibitory effects of matrix metalloproteinases. Intriguingly, this interpretation has been challenged by the consistent observation that increased expression of TIMP-1 is associated with poor prognosis in virtually all cancer types including lung cancer, supporting a tumor-promoting function. However, how TIMP-1 is dysregulated within the tumor microenvironment and how it drives tumor progression in lung cancer is poorly understood. We analyzed the expression of TIMP-1 and its cell surface receptor CD63 in two major lung cancer subtypes: lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), and defined the tumor-promoting effects of their interaction. We found that TIMP-1 is aberrantly overexpressed in tumor-associated fibroblasts (TAFs) in ADC compared to SCC. Mechanistically, TIMP-1 overexpression was mediated by the selective hyperactivity of the pro-fibrotic TGF-β1/SMAD3 pathway in ADC-TAFs. Likewise, CD63 was upregulated in ADC compared to SCC cells. Genetic analyses revealed that TIMP-1 secreted by TGF-β1-activated ADC-TAFs is both necessary and sufficient to enhance growth and invasion of ADC cancer cells in culture, and that tumor cell expression of CD63 was required for these effects. Consistently, in vivo analyses revealed that ADC cells co-injected with fibroblasts with reduced SMAD3 or TIMP-1 expression into immunocompromised mice attenuated tumor aggressiveness compared to tumors bearing parental fibroblasts. We also found that high TIMP1 and CD63 mRNA levels combined define a stronger prognostic biomarker than TIMP1 alone. Our results identify an excessive stromal TIMP-1 within the tumor microenvironment selectively in lung ADC, and implicate it in a novel tumor-promoting TAF-carcinoma crosstalk, thereby pointing to TIMP-1/CD63 interaction as a novel therapeutic target in lung cancer.

Fibrillar collagens are the most abundant extracellular matrix components in nonesmall cell lung cancer (NSCLC). However, the potential of collagen fiber descriptors as a source of clinically relevant biomarkers in NSCLC is largely unknown. Similarly, our understanding of the aberrant collagen organization and associated tumor-promoting effects is very scarce. To address these limitations, we identified a digital pathology approach that can be easily implemented in pathology units based on CT-FIRE software (version 2; https://loci.wisc.edu/software/ctfire) analysis of Picrosirius red (PSR) stains of fibrillar collagens imaged with polarized light (PL). CT-FIRE settings were pre-optimized to assess a panel of collagen fiber descriptors in PSR-PL images of tissue microarrays from surgical NSCLC patients (106 adenocarcinomas [ADC] and 89 squamous cell carcinomas [SCC]). Using this approach, we identified straightness as the single high-accuracy diagnostic collagen fiber descriptor (average area under the curve ¼ 0.92) and fiber density as the single descriptor consistently associated with a poor prognosis in both ADC and SCC independently of the gold standard based on the TNM staging (hazard ratio, 2.69; 95% CI, 1.55-4.66; P

9 pages, 3 figures, 3 tables, supplementary data https://doi.org/10.1016/j.ecss.2022.108089.-- Data availability: Data will be made available on request, Human activities provide opportunistic species with abundant and predictable feeding opportunities that may shape their ecology, including their movement patterns and behaviour. Investigating human-wildlife interactions in marine ecosystems is challenging because of the logistic constraints of surveying vast and remote geographical areas. Fortunately, miniaturized biologging devices now provide the possibility of assessing the influence of human activities on marine life, particularly in the case of large-sized predators. Here, we used GPS tracking data for Mediterranean endemic Audouin's gulls, Ichthyaetus audouinii, to quantitatively characterise gulls' foraging trips and evaluate individuals' foraging behaviour in relation with fisheries. By using ca. 38,090 space-time locations (i.e., 362 foraging trips), we calculated eight flight behaviour movement metrics to describe gull's flight behaviour within foraging trips. We used these movement metrics to analyse individuals' flight behaviour in contrasting fishing activity scenarios (i.e., presence/absence of fishing activity by trawlers and purse-seiners) and in response to spatial-temporal co-occurrence with fishing vessels operating in the area. Our results showed that Audouin's gulls adapted their flight behaviour in response to fisheries. When fishing vessels were active (particularly trawlers), gulls flew faster (particularly when co-ocurring with a fishing vessel) and more directly (i.e. lower directional changes), compared to non-fishing situations or when temporally co-occurring with purse seiners. This work enhances our understanding on seabird-fishery interactions, and may contribute to further evaluations on species responses to resource shortage scenarios, such as the collapse of local fish stocks and landing obligations. Beyond this ecological information, our results may also contribute to the use of seabirds for monitoring fisheries, and help fight Illegal, Unreported and Unregulated fishing (IUU) in areas where fishing vessels cannot be monitored by other means (e.g., through Vessel Monitoring Systems -VMS- or Automatic Monitoring Systems -AIS-), This research was funded by the Spanish Ministerio de Economía, Industria y Competitividad (MEIyC; CGL 2016-08963-R) and LIFE. INDEMARES (LIFE 07NAT/E/00732). JOC was supported by Universitat de Barcelona through the PREDOCS-UB grant (2021). FR was funded by the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) and by the Ramón y Cajal programme (Spanish Ministerio de Ciencia e Innovación, RYC2020-030078-I). FR, CS and JLC also acknowledge support by the Spanish government through the project SOSPEN (grant agreements N° PID2021-124831OA-I00, Spanish Ministry of Science and Innovation)

Accurate assessment of disease extent is required to select the best primary treatment for advanced epithelial ovarian cancer patients. Estimation of tumour burden is challenging and it is usually performed by means of a surgical procedure. Imaging techniques and tumour markers can help to estimate tumour burden non-invasively. 2-[We included 66 patients who underwent 2-[wb_MTV and wb_TLG were found to be significantly correlated with serum CA125 and HE4 concentrations. The strongest correlation was observed between HE4 and wb_MTV40 (r = 0.62, p 0.001). Pearson's correlation coefficients between peritoneal carcinomatosis MTV40 and tumour markers were 0.61 (p 0.0001) and 0.29 (p = 0.02) for HE4 and CA125 respectively. None of these tumour markers showed a positive correlation with tumour load outside the abdominal cavity assessed by volumetric parameters.HE4 performs better than CA125 to predict metabolic tumour burden in high-grade epithelial ovarian cancer before primary treatment. 2-[18F]FDG PET/CT volumetric parameters arise as feasible tools for the objective assessment of tumour load and its anatomical distribution. These results support the usefulness of HE4 and PET/CT to improve the stratification of these patients in clinical practice.• In patients with high-grade advanced ovarian epithelial carcinoma, both CA125 and HE4 correlate to whole-body tumour burden assessed by PET/CT before primary treatment. • HE4 estimates peritoneal disease much better than CA125. • PET/CT volumetric parameters arise as feasible tools for the objective assessment of tumour load and its anatomical distribution.

Tumor associated fibroblasts (TAFs) are essential contributors of the progression of non-small cell lung cancer (NSCLC). Most lung TAFs exhibit an activated phenotype characterized by the expression of α-SMA and fibrillar collagens. However, the prognostic value of these activation markers in NSCLC remains unclear. To address this question we conducted a retrospective multicentric study of the prognostic value of the standard markers of activated fibroblasts. For this purpose, we conducted a quantitative image analysis of α-SMA immunostaining and picrosirius red staining of fibrillar collagens imaged by bright-field and polarized microscopy, respectively, using tissue microarrays with samples from 220 surgical patients, which elicited a percentage of positive staining area for each marker and patient. Kaplan-Meier curves showed that all TAF activation markers were significantly associated with poor survival, and their prognostic value was independent of TNM staging as revealed by multivariate analysis, which elicited an adjusted increased risk of death after 3 years of 129% and 94% for fibrillar collagens imaged with bright-field (p = 0.004) and polarized light (p = 0.003), respectively, and of 89% for α-SMA (p = 0.009). We also found a significant association between all TAF activation markers and tumor necrosis, which is often indicative of hypoxia, supporting a pathologic link between tumor desmoplasia and necrosis/hypoxia. Our findings identify patients with large histologic coverage of fibrillar collagens and α-SMA+ TAFs to be at higher risk of recurrence and death, supporting that they could be considered for adjuvant therapy. Moreover it supports that antifibrotic drugs aiming to target tumor fibrosis may be an effective therapeutic approach to improve survival in NSCLC. Citation Format: Jordi Alcaraz, Josep-Lluís Carrasco, Laura Millares, Iuliana-Cristiana Benchea, Francisco-Javier Fernández, Anabel Martínez, María José Pajares, Julio Sánchez de Cos, Ramon Rami-Porta, Luis Seijo, Josep Ramírez, Noemí Reguart, Esther Barreiro, Eduard Monsó. Stromal markers of activated tumor associated fibroblasts predict poor survival and are associated with necrosis in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3160.

Objective To evaluate the reporting of critical design issues and methods of statistical analysis in pharmacogenetic studies published in the medical literature. Study design and settings Systematic review of 65 original pharmacogenetic studies published in the literature over the last 15 years. Results The sample size determination and the planned sample size were lacking in 63 papers. The study design characterization was lacking in 43 papers. The number of patients analyzed ranged from 36 to 1400 (median=16 1 and interquartile range of 119-250). The Pearson's χ 2 test and the Fisher's test were the most common forms of analysis. Multiple statistical testing was relevant to 59 papers, but only 11 addressed the issue of multiplicity (Bonferroni correction). Sources of multiplicity were multiple association assessment (45 papers), analysis of both genotype and allelic frequencies (44), and multiple analysis methods (unadjusted and adjusted). Hardy-Weinberg equilibrium was tested in 12 of 45 papers performing allelic analysis and was fully reported in four of them. The results of association analyses were commonly reported as P values but rarely as estimates of an association measure (odds ratio or relative risk) and its accuracy. Conclusions These results show that there is considerable room for improvement in the current standards of design, analysis, and reporting of pharmacogenetic research.

A major hallmark of non-small cell lung cancer (NSCLC) and other solid tumors is a desmoplastic tumor stroma rich in activated fibroblasts and fibrillar collagens. Previous studies have revealed that these tumor-associated fibroblasts contribute to virtually all steps of tumor progression and even therapy resistance. However, our knowledge of the prognostic value of markers of activated fibroblasts in NSCLC is very scarce. To fill this gap of knowledge we conducted a retrospective multicentric study of the prognostic value of the standard markers of activated fibroblasts α-SMA and fibrillar collagens by quantitative image analysis of α-SMA immunostaining and picrosirius red (PSR) staining, respectively. For this purpose tissue microarrays from a cohort of 222 patients with early-stage (I-IIp) NSCLC recruited in Spain for the International Association for the Study of Lung Cancer TNM-16 staging project were analyzed. A percentage of positive staining area/image was obtained for each marker and patient. Kaplan-Meier analysis revealed that PSR was associated with poor survival when using data obtained from both bright-field (p = 0.04) and polarized microscopy (p = 0.002), whereas α-SMA was not (p = 0.7). Remarkably, the prognostic value of PSR was independent of TNM stage, and patients with PSR above the cut-offs exhibited a 55% (for bright-field; HR=1.55, 95%CI (1.0-2.4)) and 109% (for polarized microscopy; HR=2.09, 95%CI (1.3-3.2)) increased risk of 3 year mortality. These results reveal that the content of stromal fibrillar collagens, assessed from image analysis of picrosirius red staining (particularly using polarized microscopy) is associated with adverse prognosis independently of the tumor stage. This new prognostic biomarker may help predict which patients subject to therapeutic surgery are at higher risk of progression and death. Moreover it supports that antifibrotic drugs aiming to target stromal fibrillar collagens may be an effective therapeutic approach to improve survival in NSCLC. Citation Format: Jordi Alcaraz, Laura Millares, Josep-Lluís Carrasco, Iuliana-Cristiana Benchea, Francisco-Javier Fernández, Esther Barreiro, Anabel Martínez, Julio Sánchez, María Ángeles González-Castro, Ana Blanco, Rosa Sánchez-Gil, Mireia Serra, Ramon Rami-Porta, Jaume Sauleda, Esther Fernández, Rosario Melchor, Luis Seijo, Leonardo de Esteban, Eduard Monsó. High stromal fibrillar collagen predicts poor survival in surgical non-small cell lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1554.

In the diagnostic area, the usual setting considers two populations: nondiseased and diseased. The use of the standard ROC analysis methodology is well established. Sometimes, however, diagnostic problems inherently include more than two classification states. For example, 'yes, uncertain, no' or 'low, normal, high'. Here we consider a three-normal distribution setting and derive estimators for the optimum thresholds between states based on a cost function. These estimators can be extended for clinical contexts with more than three states. This approach is well known for the two-state setting and its advantage lies in the fact that it accounts for the specific context's properties, such as disease prevalence and classification costs. Here we calculated the variance of the estimators by the use of parametric methods on nonlinear equations and we constructed confidence intervals accounting for possible uncertainty in the threshold estimation. We conducted a simulation study to assess the performance of these estimators and the confidence intervals. Comparisons with the naive threshold estimation method of joining the distributions two-by-two and applying standard ROC techniques proved that the latter method is not reliable for all parameter combinations and should be avoided.

Reliability and agreement of measurement methods is a fundamental issue in health sciences which is not usually borne in mind. In this document the connotations of using measurement methods with error and the switchability among measurements from methods which disagree are highlighted. These implications are illustrated through examples showing up the confounding effect that measurement error can produce. Throughout the document several procedures to assess agreement and to identify the error sources are suggested. These procedures are classified according to the sort of data, quantitative or qualitative data, as well as the way of agreement is assessed, in an aggregate way by means a values or in a disaggregate way analysing separately the error sources. By means of these procedures is showed that frequently used approaches to assess agreement as the averages comparison, the correlation coefficient or the regression model appear as insufficient or inadequate approaches.