Sanju Sinha Profile picture
Sep 29, 2022 19 tweets 7 min read Read on X
Interested in aging and cancer. I did a year of literature survey on this.

Here is my list of 20 key open questions and challenges to better understand the interplay between aging and cancer. A thread 🧵👇 Image
The presence of mutated clones in aging but otherwise healthy tissues has blurred the frontier between noncancer and cancer clones.

Why the clones that accumulate with age do not generate cancers? Image
What is the molecular basis of cancer incidence increases with age beyond mutation-accumulation? Image
Clonal hematopoiesis is strongly associated with the acceleration of multiple aging-associated clocks.
How? ImageImage
Unclear how processes such as stem cell competition for niche occupancy influence the switch from a premalignant to a malignant state.

It could help identify a sub-population at high risk of multiple aging-associated diseases and thus may be a target for clinical interventions. Image
What is the link between cell competition in aging epithelia and early steps of cancer?

For context: sciencedirect.com/science/articl… ImageImage
What are the distinct paths for nonmalignant clones to transform into cancer? Image
What are the boundaries between a nonmalignant and a malignant clone? ImageImage
Why do certain accelerated aging diseases increase cancer risk (Werner syndrome) vs. some decreases them (Hutchinson-Gilford progeria syndrome)? Image
Do people with germline mutations in cancer genes (RAS, BRCA1) have a different rate of the aging clock? ImageImage
What is the ability of interventions to slow down aging effects to prevent cancer?

Five major intervention targets: Insulin growth factor pathway, the mammalian target of rapamycin (TOR) pathway, the family of sirtuins, the mitochondria and cells undergoing senescence. ImageImage
What is the best approach to measure biological age in routine clinics? Can these measurements guide cancer treatment? Can changes in these measurements during therapy predict response? Image
What are the effects of cancer treatment on the aging of various tissues, including highly dividing tissues measured via multiple biological clocks measurements? Image
What are the links between biological age biomarkers and cancer risk? Image
Both the definition and our monitoring ability of senescent cells are poor.

How do you monitor and identify senescent cells in aging tissues? Image
How the efficacy of cellular therapy (CART, T-cell transfer therapy) is dependent on the patient's age?
Does it decrease due to immunosenescence and immune aging? ImageImage
How the risk-benefit ratio for cancer treatment changes with age, and is there an inflection point? Image
Can combining senolytic drugs with existing cancer therapies affect the patient's response? Image
What is the role of pre-existing clonal hematopoiesis in frequently occurring therapy-related leukemia? Image

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More from @Sanjusinha7

Feb 4, 2023
Spending millions of $, Grail created a TCGA-like study to systematically answer the following:

What is the best cell-free DNA method to detect cancer from blood?

17 things we learned.🧵🩸
1. This study was composed of three phases, and today we will only discuss the first phase.

The goal of this phase is to answer which type of assay might give us the most insightful features to detect cancer - methylation, targeted-DNA-seq, or whole genome seq.
2. Before the dive, let's understand the problem.

Multiple current single cancer tests are simply not feasible.

After 3 years of routine cancer screening in three different organs, the cumulative risk of one false positive is 60% for men and 49% for women. No way!
Read 25 tweets
Nov 7, 2022
A lot of Machine Learning (ML) I learned during my Ph.D. was from youtube. I didn't have a guide to do this effectively and thus here it is:

A complete guide to studying ML from youtube: 13 best and most recent ML courses available on YouTube. 👩‍🏫🧵⤵️
We will start with "Stanford CS229: Machine Learning" by Andrew Ng to start and learn the following ML concepts:

Linear & Logistic Regression,
Naive Bayes, SVMs, Kernels
Decision Trees, Introduction to Neural Networks
Debugging ML Models.
youtube.com/playlist?list=…
A series of mini-lectures (~5 mins) covering various introductory topics in ML by Cassie Kozyrkov, covering:

Explainability in AI, Precession vs. Recall, Statistical Significance, Clustering and K-means, and finally, Ensemble models. youtube.com/playlist?list=…
Read 22 tweets
Nov 2, 2022
I curated a list of 28 common issues one faces while using machine learning for biomedicine research and using different kinds of omics data. I also provided guides on how to best overcome them. 🍉🧵👇
I will cover these issues and how to address them using the following 8 studies.

We will start with the five pitfalls that arise when applying supervised ML models in genetics and genomics and how to best navigate through them.
nature.com/articles/s4157…
We will next cover the eight common mistakes we make in deriving and validating predictive statistical models from high-dimensional data.
nature.com/articles/s4156…
Read 16 tweets
Oct 14, 2022
Using big data in healthcare. Here are 10 educational resources for anyone interested in building skills to analyze big data in healthcare.

Ranging from introductory to advanced, this includes courses, youtube channels, papers & online books.🧵🥑👇
We will start with a bioinfo course covering standard bioinfo to utilizing bulk/single-cell omics, big screens, precision oncology, & immunotherapy (Chp 19-26). @XShirleyLiu @joshuastarmer @tangming2005 @getz_lab @twang5

Recommend for folks using omics.
liulab-dfci.github.io/bioinfo-combio/
We will next go onto a brilliant youtube channel -- StatQuest by @joshuastarmer. It is one of the best ways to learn fundamental big data analysis way beyond their statistics. His humor and comedic timing are unmatched.
youtube.com/c/joshstarmer
Read 15 tweets
Oct 1, 2022
Our understanding of the immune system is quickly growing.

11 resources (videos and papers) covering the fundamentals and computational tools available to study the immune system. 🧵👇🔬🤒
Before we go on to learn the computational tools to quantify and measure the immune system, Let's start with a 15 mins visual overview of the fundamentals of the immune system.
Next is another 15 mins visual. This explains the cells of the immune system and their different functions that provide an immune response to an invading pathogen.
Read 14 tweets
Sep 16, 2022
Methods & data available to you are your thinking tools. While I learned the methods in my classes, I wish I knew various data available to me.

10 resources to learn almost all the big data resources available in cancer research. 🧵👇
First is my and @PengJiang20 collection of all the big data resources (data projects, data hosts, web analysis) in cancer research. (Review resulting from this: tinyurl.com/mrxpjaad) docs.google.com/spreadsheets/d…
List of 113 major papers that generated big data funded by NIH and direct link to download their processed data. Explore and search through them. gdc.cancer.gov/about-data/pub… ImageImage
Read 15 tweets

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