Achilles Therapeutics PLC (ACHL) Share Price

ACHL.....................................https://stockcharts.com/h-sc/ui?s=ACHL&p=W&b=5&g=0&id=p86431144783

Achilles Therapeutics Announces Strategic Update

ACHL new 52 week low

Research collaboration with Arcturus Therapeutics https://www.globenewswire.com/news-release/2024/05/22/2886352/0/en/Achilles-Therapeutics-Announces-Research-Collaboration-with-Arcturus-Therapeutics-to-Explore-Second-Generation-Personalized-mRNA-Cancer-Vaccines.html

It could,* but as I said still think the product doses, cell phenotype(s) and neoantigen-reactivity will play a role as well. There is data from different groups to support that.

As for the innate arm, it would be interesting to test single and dual CARs against PD-L1 and HLA-G in a select patient population https://aacrjournals.org/cancerres/article/83/7_Supplement/5965/724047/Abstract-5965-B2M-loss-of-heterozygosity-in https://elifesciences.org/articles/54854

* Back in the 2000s, Dr Rosenberg's group the US NCI tested three consecutive protocols (in patients with metastatic melanoma) to increase the levels of lymphodepletion. In the first protocol, 43 patients were treated with TIL following the administration of a non-myeloablative chemo regimen consisting of cy/flu. A second trial was then conducted in 25 patients in which the same chemo was given followed by 200cGy whole body irradiation the day before TIL administration. In a third trial in 25 patients, the total body irradiation was intensified for a total of 1200cGy. In the latter two trials, circulating CD34+ haematopoietic stem cells were administered. In all protocols high-dose IL-2 was given as well. The ORR in the three sequential protocols were 49%, 52% and 72%, respectively.

They need to add PD-L1 or CBNK to address the innate arm. More LD not going to work.

Now they dangle yet another carrot (enhanced host conditioning). I still think the product doses, cell phenotype(s) and neoantigen-reactivity will play a role as well.

https://www.globenewswire.com/news-release/2024/04/04/2857599/0/en/Achilles-Therapeutics-Provides-Interim-Phase-I-IIa-Update-on-Clonal-Neoantigen-Reactive-T-Cells-in-Advanced-NSCLC-and-Melanoma-Including-First-Patients-Dosed-with-Enhanced-Host-Con.html

Slides https://ir.achillestx.com/static-files/d1f75ff0-b8d4-4b0c-8827-0931e5b91e70

Data already delayed from Q4 '23 to this quarter. My gut feeling says the results are poor but will see.

ACHL under $2

ACHL 10Q due March 14

ACHL 10Q due March 7

Hey loser. Check out TPTI

ACHL 1.63 WILL SEND IT

ACHL new 52 week high

Presentation is tomorrow

will go match higher soon

ACHL new 52 week high

1.50s

nice 1.40s

Nice upwards movement

ACHL...HERE WE GO...PIVOT UP AHEAD AT 1.63

ACHL...NEXT BIO BEAST READY T BEAST

i like this 1

https://finviz.com/quote.ashx?t=ACHL&p=d

$ACHL Q1 catalyst and trading well below cash of $3.5 I think. I like risk reward here because of negative EV (trading under cash value)

Took a position last week around 0.98— Pharmdca (@Pharmdca) February 20, 2024

ACHL under $2

This stock has so much cash but these guys can’t keep their stock up. I think I will be exiting this situation. I think they will might loose their NASD listing as well. Brutal

How can this management let this stock trade down under a dollar when they have approximately 140 million cash in the bank. They should look for a new CEO this deal.

True, but they still have quite some way to go when it comes to manufacturing, with dose, reactivity, and phenotype all playing a role https://www.science.org/doi/10.1126/science.abb9847

More targets better than less. Frameshift mutations matter the most. Targets not enough if T cells getting exhausted anyway. They need a process similar to LuminICE

One implication is that strategies that attempt to enhance (subclonal) neoantigen burden alone could fail.

(OT): In this paper the authors also reanalysed human clinical trial data of colorectal and gastric cancers with MMRd and show that clonal, but not subclonal, neoantigen burden is predictive of response to immune checkpoint blockade (anti-PD-1) https://www.nature.com/articles/s41588-023-01499-4

Targeting Clonal Neoantigens in Cancer https://ir.achillestx.com/static-files/d8cbf4d2-0364-4cb6-8a1e-4728edcf8f4d

Some more info https://ir.achillestx.com/static-files/d2d624b2-bde8-410e-bc5c-35f18f0f67f3

New Immunogenicity Prediction Application of its AI-Powered PELEUS™ Platform Uniquely Identifies the Most Potent T Cell Antigens https://finance.yahoo.com/news/achilles-therapeutics-immunogenicity-prediction-application-110000181.html

“HLA loss is an important mechanism of immune escape in cancer, and neoantigens that are only presented by HLA alleles that are lost in a tumor are unlikely to represent effective therapeutic targets. By determining which specific HLA alleles might have been lost, we can focus therapeutic efforts on neoantigens that are much more likely to elicit a response,” said Dr Sergio Quezada, Chief Scientific Officer of Achilles Therapeutics. “Crucially, the method described in the patent uses sequencing data that is commonly available for tumors, so both the neoantigen identification and the detection of HLA loss can be performed from the same sequencing data. We are currently using this technology within our PELEUSTM bioinformatics platform for research purposes and look forward to determining how to best use it to guide decisions in our clinical trials and beyond.”

The method described in the patent relies on the calculation of an allele-specific copy number for HLA alleles by aligning sequence data to a patient specific reference rather than a standard genomic reference. The patent covers research performed by Achilles co-founder Prof. Charlie Swanton and his academic team, first published in Cell 2017 https://www.cell.com/cell/fulltext/S0092-8674(17)31185-6

https://finance.yahoo.com/news/achilles-therapeutics-announces-grant-us-110000522.html

''During the development of our clonal neoantigen T cell therapy (cNeT) for treatment of solid tumours, we identified and screened circa 10,000 clonal neoantigens for T cell reactivity using cells grown from tumour infiltrating lymphocytes. Using this unique data, we developed and validated an AI method for predicting neoantigen immunogenicity, significantly outperforming existing tools. This technology has broad applicability for optimising target selection across all types of personalised neoantigen therapies.'' https://www.immuno-oncologyeurope.com/t-cell-therapy

A virtual panel will take place on Thursday, Oct 13, at 12:30pm ET / 5:30pm UK and will be moderated by LifeSci Partners Managing Director, Neil Canavan. The panel will highlight neoantigens as valuable targets in immunotherapy, neoantigen discovery, selection, and prediction, and tumour-infiltrating lymphocyte therapies as a platform for mobilising neoantigen reactive T-cells https://lifesci.rampard.com/WebcastingAppv5/Events/eventsDispatcher.jsp?Y2lk=MjA0Ng==

Link to webcast https://onlinexperiences.com/scripts/Server.nxp?LASCmd=AI%3A4%3BF%3AQS%2110100&ShowUUID=01B1A59F-833A-474F-A9FF-11C255EAAAE2&LangLocaleID=1033

AI model will be great for diagnosis, chronic diseases mgt., not treating cancer progressing rapidly.

The data model is not biased compared to hospital protocols which are profit driven. Just look at the covid horse paste/do nothing fiasco. How many elderlies could have been saved with their parasites wiped out?

I do think AI is overhyped, but not machine or deep learning https://aacrjournals.org/cancerdiscovery/article/12/2/372/678469/Functional-Precision-Medicine-Provides-Clinical

But the key is how each company plans to continue to enhance their platform(s).

Deep learning is hype. AI is modeling if you understand how neural networks work.

PELEUS was designed and trained on validated data from the TRACERx study. It is the largest longitudinal patient data set with 3,200 tumour multi-regions (both primary and met sites) collected from 795 NSCLC patients over five years.

The predicted clonal neoantigens are further validated prospectively with patient samples (over 120 for different types to date). Also, deep learning algorithms are being used to enhance the prediction of neoantigen immunogenicity. So I think this will improve as times goes on. The next update will be in 2H with higher-dose cNeT (process two) and in combo with an anti-PD-1 (both process one and two).

bounced off the low from Mar 07 2022 2.7301

amazing how these things work

#RobotTrading

It took 40 years for neural network to do skin deep facial recognition. from 2X2 to 300X300 just to solve 5 holes visualization. It will take multiple 3000X3000 to see anything in TME.

5055 - Precise segmentation of growth patterns in TRACERx lung adenocarcinoma https://www.abstractsonline.com/pp8/#!/10517/presentation/18433

5636 - V-delta-1 T cells are resident in the human lung and associate with survival in patients with non-small cell lung cancer in the TRACERx Study https://www.abstractsonline.com/pp8/#!/10517/presentation/18670

5710 - Identification of convergent gene repression mechanisms through integrative genomic and DNA methylation analysis in TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/18766

5818 - Features of cancer cachexia in non-small cell lung cancer: Insights from the prospective TRACERx study https://www.abstractsonline.com/pp8/#!/10517/presentation/18790

6080 - The heterogeneity and evolution of lung neuroendocrine tumors within TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/18959

6091 - Evolutionary characterisation of lung adenocarcinoma pathological subtypes in TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/18970

6113 - Spatially resolved biomarker detection on single cells in TRACERx using multiplex imaging https://www.abstractsonline.com/pp8/#!/10517/presentation/18032

6217 - TP53 loss with whole genome doubling mediates heterogeneous intra-patient therapy response in EGFR-driven lung adenocarcinoma: A TRACERx study https://www.abstractsonline.com/pp8/#!/10517/presentation/19053

LB504 - Automated grading of growth patterns in lung adenocarcinoma-from TRACERx to LATTICe-A https://www.abstractsonline.com/pp8/#!/10517/presentation/19990

Lung cancer evolution and its prognostic impact https://www.abstractsonline.com/pp8/#!/10517/presentation/435

692 - Patient-derived co-cultures of TRACERx lung cancer organoids and autologous T-cells reveal heterogeneity in immune evasion between cancer subclones https://www.abstractsonline.com/pp8/#!/10517/presentation/13698

645 - Heterogeneity of immunotherapy biomarkers in the TRACERx non-small cell lung cancer multi-region lung cancer cohort study https://www.abstractsonline.com/pp8/#!/10517/presentation/12564

674 - Tracking the transcriptome of lung cancer-associated fibroblasts within the TRACERx lung study from patient to culture models reveals phenotypic plasticity and instructive cues from cancer cells https://www.abstractsonline.com/pp8/#!/10517/presentation/13235

1211 / 7 - Allele-specific copy-number based deconvolution of bulk tumour RNA sequencing data from the TRACERx study https://www.abstractsonline.com/pp8/#!/10517/presentation/15832

1394 / 25 - Pervasive allele specific transcriptional repression of the class I and II HLA genes in TRACERx non-small cell lung cancer https://www.abstractsonline.com/pp8/#!/10517/presentation/14639

1591 / 6 - Convergence of antigenic diversity and Tex-cell stability fatally constrains immune surveillance in non-small cell lung cancer (TRACERx) and HIV-1 infection (Protocol C) https://www.abstractsonline.com/pp8/#!/10517/presentation/14124

1603 / 18 - Genomic transcriptomic evolution in TRACERx lung cancer and metastasis https://www.abstractsonline.com/pp8/#!/10517/presentation/14137

1699 / 16 - SignaTree: A tool to identify evolutionary trajectories of the activity of mutational processes in TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/14141

1926 / 5 - Machine learning-enhanced image and spatial analytic pipelines for imaging mass cytometry applied to the TRACERx non-small cell lung cancer study https://www.abstractsonline.com/pp8/#!/10517/presentation/14797

2197 - Targeted cancer therapy induces APOBEC fueling the evolution of drug resistance https://www.abstractsonline.com/pp8/#!/10517/presentation/13694

2144 - Holistic sampling of clonal dynamics using cfDNA in lung TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/12566

2784 / 18 - A robust copy number based clonality classification for multiple pulmonary tumors in routine pathology practice by shallow next generation sequencing of formalin fixed clinical specimens https://www.abstractsonline.com/pp8/#!/10517/presentation/12713

3043 / 1 - Exploring the microbial landscape of NSCLC through TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/11523

3096 / 3 - Multi-region patient-derived xenograft models from non-small cell lung cancer patients enrolled in lung TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/14356

LB153 / 6 - Clinical relevance of spatial intermixing of growth patterns and immune infiltration in lung adenocarcinoma-from TRACERx to LATTICe-A https://www.abstractsonline.com/pp8/#!/10517/presentation/20375

3626 - Genomic evolutionary patterns in matched pre-invasive and invasive lung disease in TRACERx https://www.abstractsonline.com/pp8/#!/10517/presentation/16334

3609 - Defining extrinsic and intrinsic mechanisms of immune evasion in TRACERx using imaging mass cytometry https://www.abstractsonline.com/pp8/#!/10517/presentation/13896

3792 / 5 - TRACERx: Mapping the evolution of metastases in non-small cell lung cancer https://www.abstractsonline.com/pp8/#!/10517/presentation/14147

The company will host a KOL webcast & fireside chat moderated by Joe Catanzaro on April 14 at 10:30am ET with Drs. Charlie Swanton, Sergio Quezada and Iraj Ali to discuss the TRACERx study and highlight select AACR posters and presentations (of thirty-one).

ADXS also found numerous frame shift mutations common on tumor types, which resulted in long peptides in their HOT vaccine. Are clonal neoantigens same as frame shift mutations?

No, but the data its trained on is designed to distinguish tumour DNA from non-tumour DNA and clonal from sub-clonal neoantigens*. For any clonal sequences, they create peptides and use them for (patient-derived) DC co-culture, before T-cells (both CD4+ and CD8+) are added, reactivates are identified, and then selective expansion of them.

In 2H there will be additional low-dose mono data, higher-dose (Process 2) mono data, and combo data (plus Opdivo in melanoma, NSCLC is slightly behind).




* https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001906 https://www.nejm.org/doi/full/10.1056/NEJMoa1616288 https://www.nature.com/articles/s41586-019-1032-7 https://www.nature.com/articles/nature22364

Computer prediction has not worked for ADXS and many other bios