Lung Cancer - Science topic

I would like to obtain a database (digital or text) for lung cancer related to statistics or symptoms for patients and healthy people?

This article 《Low Risk of Hyperprogression with First-Line Chemoimmunotherapy for Advanced Non-Small Cell Lung Cancer: Pooled Analysis of 7 Clinical Trials》 can have 7 clinical Trials to analys, does that mean these 7 trials start by themselves or there is a way to get information like that?

One of the recent paradoxes is the sharp increase in lung cancer cases among non-smoking women under the age of 50, which has raised concerns among specialists. While some scientists attribute this trend to random genetic mutations, often referred to as the "bad luck" theory, our preliminary investigations emphasize the role of environmental factors—particularly the greater amount of time women spend indoors and, consequently, their increased exposure to radioactive radon gas.

Could it be that "bad luck" simply refers to factors we have yet to fully understand?

Hello, I have some questions in my research.

I try to do research about a specific gene in lung cancer. In RNA seq bulk analysis(the tissue of lung cancer), this gene may contribute to lung cancer, so I want to know if this gene is associated with lung cancer.

But now I have problems. Because in the protein atlas, the number of cell lines in lung cancer is very small. My advisors suggest me to study other cell types (like immune cell) than tumor cells.

Some basic information about the gene is that it's about enzyme, ECM associated, and high expression in lymphoma and leukemia.

As a result, there are some questions. First, I want to ask, besides tumor cells and immune cells, what are the other cell types? Second, in my case, is it suitable to study tumor cells(lung cancer)? Or I need to try immune cells(like NK cellss) or connective tissues(like CAFs)?

Hope someone give me some advices!

Thank you.

The detection of lung cancer is a critical fact or in enhancing patient survival rates. The integration of intelligent computer-aided systems can significantly aid radiologists in this endeavor. The present study centers on the development of a machine learning-oriented methodology aimed at detecting lung cancer through the analysis of text-based medical data extracted from authentic medical reports. The present dataset encompasses a range of machine-learning algorithms that have been utilized for binary classification purposes. The findings of this study indicate the capability of machine learning algorithms in the prompt identification of lung cancer, thereby facilitating enhanced diagnosis and timely intervention.

My aunt is a patient with advanced lung cancer. The current treatment is very simple, just combining traditional Chinese medicine with taking Zotinib. I would like to ask if there are better treatment methods or drugs?Thank you all here.

I've been having difficulties inducing a proper amount of lung nodules in a KRAS-driven (KrasLSL-G12D) conditional mouse lung cancer model following this protocol:

Conditional mouse lung cancer models using adenoviral or lentiviral delivery of Cre recombinase

This is the Nature Protocol paper from Tyler Jacks lab that I have been using as a reference

Reagents

Add 2.5 uL of Ad5CMVCre to 121.9 uL of MEM and mix well.

Add 0.6 uL of CaCl2 and mix well.

Let this mixture sit for ~20 minutes before use.

I have been using 2.5 x10E7 pfu for my experiments. Here are my questions:

1. When making the virus prep, is it a homogeneous solution after calcium phosphate precipitate formation? I wonder if one needs to flick the tube or pipette to mix it well after sitting on ice for 20 minutes and before giving it to the mice.

2. Can I make a "master mix" virus prep for all mice dosed on the same day? Or should I prepare one tube per mouse?

3. Is there a specific reason one must use 2M CaCl2 when making virus prep? Because sometimes 0.6 uL could be hard to pipette.

Hi everyone,

I need help and yuoue experience!!!

What kind of cell culture contamination is it?

Video attached: The cells are lung cancer cells that are thawed from -80°C fridge and we known that are probably alla dead, but we see this strange, non identify object, that move and change shape.

I never seen this kind of bacteria before. I always seen the classical sand contaminaion with torbid medium.

Thank you for any information or suggestions

Valeria

Why WES and RNAseg analyses of the primary lung cancer tissue give different percentage of VAF for the same gene?

Nan-Haw

How to download Lung cancer (LUSC) gene expression data which includes tumor tissue samples and corresponding control tissue samples from TCGA(https://portal.gdc.cancer.gov/repository). Any information or resources you could provide. I look forward to your guidance. Thanks in advance.

Cancer as of now is not an infectious disease. The Papillomavirus, virtually, causes all cervical cancers and yet cervical cancer is "not considered" as an infectious disease? Some lung cancers of the smokers could, justifiably, be caused by papilloma virus and or other microorganismes, then why at least these cancers are not labeled as infectious diseases?

I have a dataset from lung cancer images with 163 samples (2D images). I use the fine-tuning of deep learning algorithms to classify samples, but the validation loss did not decrease. I augmented the data and used dropout, but the validation loss didn't drop. How can I solve this problem?

I am growing small cell lung cancer suspension cells. How do I separate dead cells from live cells while splitting the cells after confluency in flask?

Like in Lung cancer how b cells are getting affecting, so just want to how and what are the complications B cells are facing regarding different type of cancerous cells

Is there a link between breast and lung cancer?

Does one lead to another or do they occur simultaneously?

When an individual is diagnosed of breast cancer, is it a must for the person to have lung cancer?

Generally, does a type of cancer leads or precedes another type?

In the past two years, Oncology Research has witnessed remarkable progress in the field of lung cancer research, with numerous innovative and prospective articles published between 2022 and 2023. From these we have carefully selected a range of papers covering different areas, including the diagnosis, treatment and prevention of lung cancer. By sharing these research breakthroughs, we aspire to provide readers with valuable insights and inspiration, fostering a deeper understanding of the ongoing advancements in lung cancer management.

The article is as follows：

Thank you for your time.

Sincerely,

Oncology Research Editorial

Objective of the study: Evaluate whether normal bronchial epithelial cells acquire invasiveness following exposure to particulate matter.

Initial approach: Expose the BEAS2B cell line to PM10 at concentrations of 50ug and 75ug for 48 hours. Subsequently, perform a wound healing assay and an invasion assay using matrigel.

Problem encountered: Post exposure, a significant number of cells died, resulting in inadequate cell viability. This has hindered our ability to observe if the non-malignant BEAS2B cells acquired invasiveness.

Query: Are there strategies to maintain cell viability post PM exposure while ensuring the effects of PM are still observable in the cell line? Would it be advisable to modify the PM exposure conditions, such as by reducing PM concentration and prolonging the exposure duration? Should I provide break for the cell lines to recover and reinitiate the PM exposure?

WHO & ILO jointly declared for elimination of silicosis by 2030. But unfortunately we do not see any initiative or effort from both ILO as well as WHO for elimination, the reason of which is not understandable. By eliminating silicosis, silico-tuberculosis as well as silica induced other comorbidities including lung cancer can ne prevented. Can anybody explain why ILO & WHO are so silent about it after declaration?

I mean, which physiological or immunological parameters/markers that I need to study to know the effect of using immunotherapy in the patients with lung cancer?

Any suggestion for research would be helpful?

Thanks for your time..

I mean, which physiological or immunological parameters/markers that I need to study to know the effect of using immunotherapy in the patients with lung cancer?

Any suggestion for research would be helpful?

Thanks for your time..

I need to perform staining of A549 lung cancer cells using Alexa flour 594 phalloidin. Can anyone explain the protocol

Hi,

I'm working on lung cancer cells, LLC1 (CRL-1642, ATCC) but I'm not familiar with it.

which media and what kind of FBS are good for LLC1? or are there anything important I need to know?

Many thanks.

Hello everyone

How can I find and select new cancerous marker from genetic/genomic panel of lung cancer?

If I have the total burden of disease e.g. mortality of lung cancer in adult age 25+ in DALY, can I estimate the lung cancer DALY due to air pollution PM2.5 using attributable proportion calculated from WHO AirQ+ software? If possible, what is the equation? Thank you

I need journals andbooks on the topic

I have found a significant gene (BIRC5) between lung cancer tumor and adjacent normal samples. In the literature, it is mentioned that BIRC5 (an anti-apopotic gene) is generally upregulatd is most solid tumors. But unlikely, in my case I'm getting its expression as downregulated in tumor samples as compared to normal. Is it possible to get expression status of a gene altered in biofomatics analysis as compared to wet-lab results? Does this depend on sample size or type of dataset?

Hi all,

I'm growing primary basal cells from lung digests, and was wondering if anyone has recommendations for cell freezing media for primary lung basal cells.

Previously I have been using Cryostor CS10, however I'm finding quite costly and would like to make my own.

My expansion media is Pneumacult EX Plus.

Many thanks,

Sam

I am first semester PhD Cancer Biology student . I would like to perform in vivo analysis of nanoparticles that I have prepared using plant extracts on lung cancer cells. Can someone help me with the methodology to be followed or feasibility of this research in terms of in vivo analysis?

Dear All, I am going to detect MMP2 and MMP9 in different cancer cell lines after drug treatment, like breast cancer and lung cancer. However, I cannot get bands in western blot using both cell lysate and culture medium. I guess the antibodies did not work so I just bought new ones. The question is do MMPs difficult to detect by WB and how can I improve this? I also find someone use zymography to detect MMPs, is it a better way or not? Thanks in advance!

The BEIR VII Phase 2 Report presents the lifetime attributable cancer risk for incidence and mortality:

BEIR VII Report: https://nap.nationalacademies.org/download/11340 (You can choose Download as guest), Tables 12D-1, 12D-2 and 12D-3, pages 311-312

The values for mortality from lung cancer are slightly greater than the values for incidence. How is this possible? Thanks for answers.

I am culturing some patienet-derived primary lung cancer cells in vitro .Recently I found there was some bubbles in several flask of tumor cells, with no matter high or low passage numbers.Some of these have no inner strcture, but some of these bubbules have tumor cells inside.Also I could see some bubbles floats in medium.So is this phenomenon an appearance of cell senescence? I was wondering does it means these cells are in a bad state?

Thank you for your answer!

Hi,

We are doing focused scSeq of lung cancer and we need a panel of genes to identify and differentiate the lung epithelial cells from other cell types of lung. What genes would be useful?

Best regards,

Morten

I would like to ask whether there will be a worse result of the immunocytochemical reaction, which will be carried out on archival materials (2006-2008): cytological smears of lung cancer, stained by Pappenheim and Papanicolaou?

I am updating my earlier review on the role of Fluoride doped Hydroxyapatite in Cancer and my current focus is on Psammoma Bodies which have been found, and identifed as high risk, in a very wide range of Cancers. These include Cancers of the Bone, Spine, Brain, Choroid Plexus, Dura Mater, Gliofibroma, Medulloblastoma, Meningioma, Cervix and Endometrium, Ovary, Kidney, Lung, Mesothelioma, Pancreas, Skin, Hemangioendothelioma, Olfactory Neuroblastoma, Duodenal Somatostatinoma, Stomach and Thyroid. Early studies did not have the benefit of advanced analytical techniques, or did not even consider the Fluoride content or composition of the mineralization. Can anyone help by supplying analytical data based on Raman spectroscopy, neutron activation, x-ray or wet analysis?

I have lung cancer biopsy slides that show auto-fluorescence (FITC) how do I quench or overcome the fluorescence?

Do you think it is possible to study the spread of lung cancer in the parenchyma only by cytological and immunocytochemical methods (if access to histological material is limited)?

Hello, I have one problem with the sequence of DNA which would be used as the evidence for lung cancer Please help me and guide me about this problem.

Thank you.

Would like to get Remi Mito et al 2020 full article under the following title: Clinical impact of TROP2 in non‐small lung cancers and its correlation with abnormal p53 nuclear accumulation.

Many thanks

Kanglaite (KLT) is a type of Chinese herbal medicine. It comes from the seeds of a tropical Asian grass called Coix. It isn’t a treatment in the europe or USA but doctors in China have been using it to treat cancer since the mid 1990s.

Rajan and Pandey have recently investigated the effects of low doses of alpha particles on human cancer cells. These researchers observed that in contrast to the tumoricidal effects seen at high doses, human lung adenocarcinoma (A549) cells irradiated with low doses of alpha radiation were more proliferative and tumor volume increased both in vitro and in vivo. The results derived from the paper authored by Rajan and Pandey pose a number of interesting questions.

Rajan and Pandey did not focus sufficient attention on other key applications of their findings in radiobiology and radiotherapy. For example, a key question is whether we can conclude that patients with lung adenocarcinoma should decrease their indoor radon levels. Although we have tried to answer this question in our LTE, I believe there is still room for exploring different aspects of the findings of these researchers.

I need to test if a certain value (e. g. the number of lung cancer patients) has changed over time (e. g. over the last 30 years). I want to observe time trends over the years – when did the numbers increase, when did they decrease, and what is the overall trend over time.

Good time dear

Which extraction kit for DNA or RNA from tissue? Best quality and higher yield...

Thanks

Best regards

Anyone with experience in the model of lung cancer induced by intraperitoneal injection of NNK in mice? What dose to use? where can I buy NNK?

I would like to sort from a fresh specimen of lung cancer Non-Small Lung Cancer cells and cancer-associated fibroblasts to establish two different cell cultures. Which markers should I use?

Thank you in advantage

Adriana

Which database shall i use for lung cancer detection which contains normal lung ct images and cancerous LUNG CT images ? please provide your valuable information regarding this

thanks in advance

Wellington Pinheiro dos Santos, Federal University of Pernambuco, Brazil

Juliana Carneiro Gomes, Polytechnique School of The University of Pernambuco, Brazil

Maíra Araújo de Santana, Polytechnique School of The University of Pernambuco, Brazil

Valter Augusto de Freitas Barbosa, Federal University of Pernambuco, Brazil

The series of books Intelligent Systems in Radiology aims to present the principles and advances of diagnostic techniques in Radiology based on Artificial Intelligence, from the perspective of the advent of Digital Health. The series consists of three books. Each of them is divided into two parts: one dedicated to theoretical foundations and the other to radiological applications in the real world. This call for chapters is dedicated to the first volume.

The first book, Intelligent Diagnosis of Lung Cancer and Respiratory Diseases, is dedicated to the diagnosis of diseases of the respiratory tract or those that seriously affect the respiratory system. In the first part, the physiological foundations of the respiratory system and the formation of radiographic images and x-ray computed tomography are presented. Principles of respiratory diseases are also presented, including lung cancer, viral and bacterial pneumonia, tuberculosis, and Covid-19. In addition, the principles of pattern recognition and machine learning and the main theoretical and practical tools are also briefly presented, and libraries in the programming languages ​​Python, Java and Matlab are also commented. The second part presents innovative works and systematic reviews of intelligent applications in the diagnosis of lung cancer, tuberculosis, viral and bacterial pneumonias, and Covid-19.

This book series is intended for readers interested in intelligent systems to support diagnosis in Radiology. The series is composed by three books. The first one, Intelligent Diagnosis of Lung Cancer and Respiratory Diseases, the focus of this call, is dedicated to diagnosis of respiratory diseases. The second book covers the diagnosis and treatment of neurodegenerative diseases. The last book is dedicated to Neuroscience applications, from clinical to affective computing applications. All books present comprehensible theoretical fundamentals both from clinical and computer engineering perspectives.

This book is intended to everyone who needs to understand how radiological images, neuroscience and artificial intelligence could work together to generate solutions in the context of intelligent diagnosis support and applied neuroscience and how intelligent systems could process and analyze images to improve early diagnosis and, consequently, prognosis of diseases.

Contributors may submit proposals on topics that include, but are not limited to, those listed below. The chapters may take various forms.

Part I: Fundamentals

1. Physiology of the respiratory system

2. Fundamentals of x-ray images and computerized tomography

3. Principles of lung cancer and respiratory diseases

4. Principles of pattern recognition and machine learning

5. Principles of image processing

6. Computer-aided image diagnosis

7. Computational tools and tutorials on Python, Java and Matlab

Part II: Applications

1. Lung cancer

2. Tuberculosis

3. Viral and bacterial pneumonias

4. Covid-19

5. Emergent imaging techniques

Potential contributors are invited to submit, on or before January 31, 2021, an abstract of 300 – 400 words proposal (excluding references) that presents the intended contributions of their chapter, intended approach and methodology.

In addition, authors should provide the following:

· Proposed titles of their chapters

· The theme (see above) of their intended chapters

· Full names

· E-mail addresses and

· Affiliations

Chapters submitted must not have been published, accepted for publication, or under consideration for publication anywhere else.

Proposals and full chapters should be submitted via EasyChair according to the following link:

By February 15, 2021, potential authors will be notified about the status of their proposed chapters. When accepted, the authors will receive further information regarding the submission process, including the formatting guidelines.

Full chapters should be submitted on or before April 16, 2021 in a single attached Word or LaTeX file with the Copyright Letter. References should follow IEEE standards. The authors should follow the formatting rules in this link:

Final submissions should be approximately 4,000-5,000 words in length, excluding references, figures, tables, and appendices. All chapters will be peer-reviewed. No fees will be demanded from the authors at any stage.

Full chapters are expected to be at least 25 pages in length, font size of 10pt for the abstract, 12pt for the body text, and single-spaced paragraphs.

• January 31, 2021 - Proposal submission deadline (300-400 words)

• February 15, 2021 - Notification of acceptance of proposal

• April 16, 2021 - First draft of full chapter submission

• April 30, 2021 - Revision submission

• May 14, 2021 - Final acceptance notification

• December 2021 - Publication

The book will be published by Bentham Science Publisher until December 2021.

Please address any questions you may have to Prof. Wellington Pinheiro dos Santos - wellington.santos@ufpe.br.

I am working on lung cancer. Till now I have studied the metastasis, only in cells. I want to use animal model.

what is the best mouse model for lung cancer study? No Knockout Mice We Have Simple Strain?

I wish to analyze whether progression free survival can be used as a surrogate for overall survival in lung cancer. I want to use clinical data from TCGA database. however, I am having a problem how to extract the data and how to analyze the data.any advise or suggestions,would be most welcomed,

I am working on mechanism study of some anticancer compounds using A549 and H460 NSCLC cell lines. I want to check if my compounds are non-toxic to normal cell or not. Some researcher use human normal lung fibroblasts HEL-299 and MRC-5 cells while others use normal cell lines that don't belong to lung tissue. I want to use only normal lung cell, not from other tissue. Can anyone suggest me which one is the best normal lung cell line model?

How to get access to LYON19 dataset? histopathological image dataset of Lymphocytes provided by LYON19 challenge is not accessible from its challenge site https://lyon19.grand-challenge.org/Background/ .

My investigation is related to measures countries (Mexico for example) have taken focusing on lung cancer prevention, considering sustainable environmental policies.

Do you know any normal mouse lung cell lines other than MLE 12 (which transformes Tumorogenic)?

Studies of underground miners exposed to radon have consistently demonstrated an exposure-related increase in lung cancer risk; based on this evidence, radon is classified as a known human carcinogen

Though tobacco is considered to have high levels of toxic compounds, nicotine being the most abundant, from my observations those who chew tobacco have up to 99% not suffering from dental problems. Comparatively with smoking tobacco those who chew are not at risk of lung cancer, or throat cancer.

What are the differences between H1299 and A549 lung cancer cell lines?

and what is the best choice to use in scientific researches?

It had been seen a quite considerable positive tendency in African-American people to be least susceptible to developing lung cancer in specific. Can this be a cultural associated tendency?

I was wondering if our immunological system possessed any kind of immunological defense to prevent lung cancer and how it deferred (if any) from any other kind of immunological reaction.

Looking for answers to the following questions:

What are the immunity mechanisms in relation to the protection against lung cancer?

What is the difference in energy obtention between normal cells and cancerous cells?

How does the body protect itself against a cancerous cell or formation?

How does stress affect the cells, and how can it be linked to causing cancer?

How can we change so that environmental factors in lung cancer can decrease?

How can biomimicry help us in the fight to cure lung cancer?

Hi, Very new to survival analysis here. I am now trying to correlate the gene expression level with survival and prognosis for patients with lung cancer, and I want to run a cox regression analysis on it. However most of the example I've encountered so far are based on discrete covariate such as sex and I know we can analyze continuous covariate using the coxph function, but I can't see how the actual plot would look like for continuous variable? For instance, for discrete variables you would have the number of regression lines correspond to the number of discrete variables. eg. for gender you'd have two lines on the graph. But what about continuous covariate? Should we first turn the continuous covariate into discrete by assigning quantiles to them? Or else I don't know how to visualize the graph. What are the pros and cons for doing so?

Thanks!

I'm aware of respiratory system deseases caused by crystalline silica (C-SiO2), but does elemental silicon (nanostructured silicon) have negative effects on lungs? Are there any article and experimental reports in this topic? I'm working with this material and I want to know about safety cares that have to be taken.

I am looking to develop a model for lung cancer metastasis in C57 mice. I used a tail vein injection method but the model did not work for me. Do you think an injection of saphenous vein can help me? Or should I look for another way? Thanks a lot

Hello everyone,

Is it possible to expand primary tumor cells in 2D culture? Are they adherent cells? Do you have any experience especially with culturing non-small cell lung cancer in 2D?

Thank you.

Hello,

I used to work on gliomas and used several websites for RNA-seq such as Gliovis, geoprofile GDS1962 and many others to explore the mutation and the differential expression of genes in gliomas subtypes. Currently, I started working on lung cancer and I need to perform the same analysis of the gees expression in different lung cancer (adenocarcinoma) subtypes. Does anyone has an idea about a good website to extract the datasets that I want?

Thank you

We sequenced the exons of some healthy persons, and we know that some of them run the risk of developing cancers. Is it feasible to develop preventive cancer vaccines? The vaccines would secure them from developing lung cancer, liver cancer, etc. Thanks.

I'm working on a report that suggests an alternative device for patients with lung cancer.

This figure is from "A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade" of Nature Medicine. They did H&E staining on human tumor slide. The white arrows point to the tertiary lymphoid structure (TLS), does anyone know why haematoxylin (purple) can stain for TLS and eosin (light pink) stained for cancer cells in this figure?

I don't really understand the mechanism.

Can someone help me? Thanks so much!

I'm working on a report about alternative devices for patients with lung cancer.

I'm writing a paper for my Biology class and my teacher said that there is a link between your ethnicity and the odds of you getting lung cancer, especially with black people (outside the differences in socio-economic circumstances), supposedly they're more prone to get it, but every paper I've read on the matter says the exact contrary.

Is there any research on molecular level lung cancer in Iraq? Especially with regard to the gene of Kiras? Does it have any relation with the progression of the disease and the progression of cancer in it and its development from the first level to the fourth level?

levelˈlevel

Hello researchers,

I am trying to check the effect of a chemokine on lung cancer cell (A549) metabolism. Last time I tried to induce the cells with different concentration of the chemokine (inducer) at 0,10,20,50,100 and 200ng for 24,48 and 72 hours and check the absorbance of lactic acid (LD) using the colorimetric kit. The values in triplicate at each concentration and time point vary from each other making it difficult to get any idea of what could be the possible optimum dose and/or time point.

My question is do the cells need to be starved before performing this assay? and is it reliable to check LD to describe the glucose uptake? Anyone could suggest me any change in my experimental design or can recommend me a good protocol?

This is too far from my area of expertise (theoretical physics) for me to get an idea. I saw that a paper had been published on this subject but I do not know how to interpret it:

Lai H, Sasaki T, Singh NP, Messay A, « Effects of artemisinin-tagged holotransferrin on cancer cells », Life Sci, vol. 76, no 11,‎ 2005, p. 1267-79.

Above all, if artemisinin is effective against cancer, what is it for small cell lung cancer (bronchi and lung metastases)?

Also, what are the chances of survival when coupled with cardiovascular problems (especially blood clots)?

Please answer with serious publications in support or explain to me, if possible, the publication issued if you have an opinion on it.

I am currently trying to obtain a gene knock-out in H2030 cell line (lung cancer) using CRISPR/Cas9. The transfection rate is very low (<10%) despite preparing various panels for optimization. I am using Lipofectamine 2000 and pSpCas9(BB)-2A-GFP (PX458) and pSpCas9(BB)-2A-Puro (PX459) constructs (Addgene). I am using 2µg/ml of puromycin for selection, established by a kill curve. I tried different seeding densities, lipofectamine concentrations, DNA concentrations, lipofectamine/DNA ratios, also different times of changing transfection medium to normal DMEM+10%FBS without antibiotics, as well as transfecting on different plates (6,12,24,96-well plates). I also tried CombiMag for transfection with nanoparticles on a magnetic plate, but it does not improve the transfection rate and leads to reduced viability of the cells. It seems that cells don’t really want to take the plasmid, because even the GFP signal disappears very fast (24h). I used DharmaFECT 1 to check different transfection reagent, but the results weren’t any better.

So far the “best” setup is a 96-well plate, confluency ~60%, 0,5µl lipofectamine/well + 0,8µg DNA/well in Opti-MEM, incubated for 5 hours, then medium changed to DMEM+10% FBS. Then after 24 hours medium is changed to 10%FBS DMEM with 2µg/ml puromycin for ~48h. Usually, only a few cells survive. I kinda gave up on GFP because a lot of them die when I try to detach them, even if I try to use something gentler then 0,05% trypsin in EDTA and after that, they mostly lose their fluorescence completely, so sorting them is very problematic. After screening they don’t show any differences between clones, because most likely, they are the non-transfected ones. I can’t say much about the puromycin-selected cells because they need a lot of time to grow back to confluency.

The cells were checked and they are mycoplasma-negative.

Has anyone perhaps run into similar issues with this cell line? Or maybe you know some “tips and tricks” how to improve the transfection?

I am working on a deep learning model for detecting lung cancer from lung CR images. I know that instead of creating a new model from scratch, I can use pretrained models like InceptionV3 for faster training and/or better performance.

But since most of these models are trained on ImageNet data-set, would they prove to be useful for classifying medical image data-sets like lung CR images?

Also, would cutting off/freezing the final layers and training them with my data-set work in this scenario?

Edit: I found a model called as niftynet that is specifically for medical image analysis, but my main question here is whether these popular models could be successfully used for transfer learning of medical image data-sets?

I’ve used the same normalization and chip to search a gene expression in R2 Genomics Analysis and Visualization Plataform, but I have compared very different cells (like lung cancer and melanoma). So my doubt is: is it correct/safe to say that a gene is more expressed in lung cancer, for example, than in melanoma (p<0,05) based on comparations made in R2 Genomics?

Ps: my intention is to prove this experimentally, and the results obtainned on R2 would serve as a guide for me.

thank you!

Assume that you have discovered a cDNA for an unknown gene from a lung cancer tissue which contains sequences for zinc finger domains. In comparing to the wild type allele, you notice a missense mutation in one of the zinc finger domains. You hypothesize that this

gene is a transcription factor and that this mutation alters the direct regulatory targets and plays a causal role in carcinogenesis.

My professor gave an assignment to write a research plan for this matter. Can anyone help me ?

I am planning a study on specific inflammatory biomarkers in lung cancer. This is to analyze prognostic value of inflammatory biomarkers in lung cancer (survival and disease progression).

In order to change the continuous variable (primary biomarker) into categorical variable (binary), I underwent ROC curve analysis.

I used SPSS version 20. for this evaluation.

In ROC curve anlaysis, the biomarker was plotted against survival status of the cancer patients (follow-up loss was also considered as censored). The cutoff calculated from the analysis had the highest AUC of 0.641, however p-value was not significant (p-value >=0.05).

Can this cutoff be used to change the continuous variable (inflammatory biomarker) into categorical variable (high/low risk)?

If the validity of this cutoff should be questioned, what alternative cutoff can be used (median value? quartile?)?

What is the most suitable animal model for lung cancer using the CD1 mice? Exposure to B[a]P? for how long at what consentration?