Pathological and Nuclear Medicine Factors for Prognosis in Lung Carcinoma

Section 1:title and overview Title: Relationship between histopathological features, mutation status, 18F-FDG PET/CT radiomic imaging parameters as well as clinical outcome in patients with treatment-naïve non-small cell lung cancer(NSCLC).

Overview: Nowadays, the most increasingly rapid incidence rate among all tumors is lung cancer, which shows the highest morbidity rate. According to types of tumor cells, lung cancer is divided into two categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the latter one includes squamous cell carcinoma, adenocacinoma and large cell carcinoma. The treatment methods are different according to TNM stages, mainly including surgical resection, focal therapy, radiotherapy, chemotherapy as well as immunotherapy. Despite improvements in drug development and treatments for NSCLC patients, five-year survival rates remain unacceptably low, because many patients present with advanced stages at initial diagnosis, with resistancy to therapy and with distant metastases. So an effective way to improve low survival rate is to increase diagnose rate in early stage, to predict whether patients will have benefits from the therapy and to determine probability of distant metastases. Positron emission tomography (PET)/ computed tomography (CT) plays an increasing clinical role in the management of many cancer patients, because it shows additional value in tumor staging, response assessment, prognosis and prediction of treatment response.

Currently, clinical predictive results of PET/CT imaging texture analyses have been obtained in a wide variety of malignancies, such as high-grade gliomas, breast cancer, lung cancer, metastatic colorectal cancer. Most of these studies have shown a significant relationship between PET/CT textural imaging data and patient's clinical outcome. More specifically, a number of NSCLC studies correlated diver gene and a series of PET/CT radiomic imaging parameters, in order to predict clinical outcomes of NSCLC patients.

However the results are somehow controversial and there is no standardization regarding calculation of PET/CT imaging parameters apart from standardized uptake values (SUV). Therefore additional studies are necessary.

Histopathological Lung Cancer Biomarkers:

Lung cancer biomarkers, such as gene mutation, circulating tumor cells (CTCs), have vital effects on predicting pathologic diagnosis, selecting effective therapy decisions and evaluating clinical outcomes accurately. Through the recognitions and utilizing those new biomarkers, the investigators can select the optimal targeted anticancer therapies, and develop new drugs against lung cancer.

Gene biomarkers:

Epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor member of the ERBB family, located on the short arm of chromosome 7 at the position 125. Extracellular ligand binding triggers homodimerization or heterodimerization of ErbB family receptors, phosphorylating active sites in the cytoplasmic tyrosine kinase, and activating intracellular PI3K/AKT/mTOR and RAS/RAF/MAPK pathways. EGFR signaling is critical in development and cellular homeostasis, proliferation, and growth. EGFR and its family members became the important candidates for the development of targeted therapeutics due to the expression rate, 50% in NSCLC, and the relationship between expression rate and poor prognosis.

The B-RAF proto-oncogene, serine/threonine kinase (BRAF) oncogene is located at the long arm of chromosome 7 at position 344. It is involved in the RAS-RAF-MEK-ERK signaling pathway by encoding for a serine/threonine kinase. When activated, BRAF promotes cell growth, proliferation and survival. BRAF was reported mostly in adenocarcinoma and current or former smokers. It has been reported that there are 1%-3% BRAF mutations in NSCLC, and its role as a prognostic predictor.

Anaplastic lymphoma kinase (ALK) is a tyrosine receptor member of the insulin receptor superfamily, locating on the short arm of chromosome 2 at position 2310. And ALK gene rearrangement was described in a subset of NSCLC tumors harboring a fusion of ALK and echinoderm microtubule-associated protein-like 4(EML4) gene. The chimeric protein with constitutive kinase activity encoded by the arrangement promotes malignant growth and proliferation. The EML4-ALK fusion has been detected in 3.7% to 7% of NSCLC and it has a role in prediction of prognosis.

ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) is a tyrosine kinase receptor member of the insulin receptor family and is located on the long arm of chromosome 6 at position 224. It involves in the signal pathways including JAK-ATAT3N, RAS/MEK/ERK, PI3K/AKT and so on. It was reported that about 1% to 2% of NSCLCs harbor ROS1 rearrangements. It occurs in young, female, never smokers with a histologic results of adenocarcinoma. It has a role in prediction.

Recently, an important discovery called "immune checkpoints" has aroused much more attention which means programmed death 1(PD-1) and programmed death-ligand 1 receptor (PD-L1). PD-1, belonging to the CD28 family, is a key immune checkpoint receptor expressing on the surface of the activated T, B and NK cells and plays a crucial role in tumor immune escape. PD-L1 is upregulated in different types of tumors, including NSCLC. PD-L1 delivers negative costimulatory signals and binds PD-1 to reduce cellular immune responses by inducing T-cell apoptosis or exhaustion. Blocking the PD-1/PD-L1 pathway with monoclonal antibodies is currently considered to be the most promising approach, offering durable activity and long-term survival outcomes. The study by Zhang et al. showed that the association between PD-L1 expression and prognosis is dependent on ethnicity. But the role of PD-L1 to predict overall survival is different in studies.

PET/CT Radiomics Imaging Parameters:

Many oncological imaging studies aimed at quantitative assessment of 18F-FDG PET and the correlation with clinical outcomes. There is an underling hypothesis on which radiomics glucose metabolism parameters rely on the existence of a relationship between extracted metabolic image data and tumor molecular phenotype and/or genotype. Radiomic parameters ideally may determine patient prognosis and predict clinical patient outcomes, being divided into two types of parameters: A) conventional PET/CT parameters and B) textural features.

Conventional PET/CT parameters include different basic metabolic parameters and volumetric parameters , such as SUVMAX, SUVMEAN, SUVPEAK, MTV, TLG, which are more or less routinely obtained and many times used in clinical patients reports.

Textural PET/CT features represent more advanced metabolic parameters and are currently not in clinical use. They are considered to demonstrate i.e. the spatial heterogeneity of malignant tumors including second-order parameters, high-order, such as GLCM, GLRLM, and GLSZM. Such advanced textural PET/CT features seem to perform better than the conventional PET/CT parameters used for imaging explanation in clinical routine. However, to date there is no consensus considering optimal segmentation methods or quantitative indices to express metabolic characteristics of a tumor leision and which textural PET/CT features can be used for clinical diagnostic purposes. Therefore, more standardized studies are needed to conclude an optimal method and to allow those parameters to be used in clinical routine diagnostics in cancer patients.

Section 2：purpose and method

Purpose:

1. to select those PET/CT radiomic imaging parameters which are most robust and repeatable after evaluation with two different published calculation methods and cross-validate using two different patient collectives (German and chinese NSCLC patients);
2. to evaluate the relationship between the type of gene mutations, conventional and textural PET/CT parameters and clinical outcomes in patients with treatment-naïve NSCLC;
3. to evaluate the relationship between CTCs, conventional and textural PET/CT parameters and clinical outcome in patients with treatment-naïve NSCLC.

Method： PET/CT radiomic imaging parameters calculation: perform post-proccessing of quality assessed, reconstructed, attenuation corrected 18F-FDG PET images and obtain conventional 18F-FDG PET/CT parameters SUVMAX, SUVMEAN, SUVPEAK, TLG, MTV using the "MM Oncology" application within the SIEMENS Syngo.via Software. Obtain textural PET/CT features, using two different previously published softwares, LIFEx and MATLAB script, to extract all textural parameters. Then compare the results of the textural parameters obtained with two different softwares and select which ones are most robust and repeatable considering the differently acquired methods. Determine which textural parameters show the same changing trends in order to remove redundant ones.

The investigators will cooperate with two well known departments (Nuclear Medicine and Pathology) specialized in oncology (Peking University Cancer Hospital) sharing anonymized patient data in NSCLC patients, in order to expand sample size, to cross-validate data and to compare similarities and differences between patients regarding different races and different regions as well as different imaging analysis methods in order to make the main results more reliable. After establishment and validation of this two-site-platform the plan is to expand analyses examining additional solid tumors such as malignant melanoma etc.

The investigators plan to extract proteins expressed by mutant genes from CTCs and analyze which gene mutations are determined. To determine the correlation between genetic mutations identified in CTCs and gene mutations identified by histopathological biopsy.

Section 3: advantage and limitation Advantage: as far as known, this is the first multisite study examining a German and a Chinese NSCLC patient collective using the same scan protocol on the same PET/CT scanner, examining different published software programs to extract and calculate 18F-FDG PET/CT textural features, making our results more understandable and more reliable and offering a possibility to cross-validate our analyses.

Limitation：the retrospective character of the study, which will not allow us to draw any definite conclusions regarding parameter selection for clinical routine purposes.